About the Role
We are looking for an AI Scientist to join our team at the intersection of machine learning and single-cell biology. This role will focus on developing and applying foundation models to large-scale perturb-seq and single-cell datasets to uncover new biological mechanisms and therapeutic opportunities. You will help design scalable ML architectures that can extract insight from high-dimensional perturbation data and integrate across multi-omic modalities.

Key Responsibilities

• Design, train, and refine foundation models tailored to perturb-seq and other single-cell datasets.
  Build pipelines for preprocessing, normalization, and integration of large-scale single-cell and perturbation data.
• Apply ML/AI approaches to model cellular responses to perturbations and identify causal biological insights.
• Collaborate with experimental biologists to align computational methods with experimental design and discovery goals.
• Develop multimodal integration approaches across transcriptomic, epigenomic, and proteomic single-cell readouts.
• Publish methods and results in top scientific journals and present at conferences.
  
  

Qualifications

• PhD or equivalent in Computational Biology, Computer Science, Bioinformatics, or related discipline.
• Strong expertise in single-cell data analysis, particularly perturb-seq 
• Hands-on experience with foundation models or large-scale self-supervised learning (e.g., transformers, variational autoencoders).
• Strong coding skills in Python, ML frameworks (PyTorch/TensorFlow), and single-cell analysis tools (Scanpy, Seurat).
• Experience in developing scalable ML methods for large biological datasets.
  
  

Preferred

• Background in causal inference, generative models, or representation learning for biological systems.
• Familiarity with multi-omics integration and cross-modal foundation models.
• Track record of impactful publications in computational biology, machine learning, or related fields.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $150,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

Essential duties include but are not limited to:

Help streamline internal processes – work directly with the Precision leadership to improve processes and efficiency; investigate optimal research techniques and implementation strategies; update existing tools and documentation to increase adherence to best practices; support development and refinement of interactive tools that use existing real-world evidence analyses.

Support ongoing research projects – assist with literature reviews on diverse healthcare topics; help with real-world evidence studies including protocol development, data programming, and results; develop interactive summaries of real-world evidence analyses; help interpret and communicate quantitative and qualitative findings to internal and external audiences; contribute to reports, results tables, presentations or peer-reviewed manuscripts; participate in client-facing activities; provide administrative project support.

Qualifications:

Required:

• Enrolled in a public health (epidemiology, biostatistics, bioinformatics), economics, data science, life sciences, or healthcare related undergraduate, or preferably, graduate program at an academic institution at the time of recruitment.

Other required:

• Proven interest in public health, life sciences, or pharmaceutical research and analytics
• Research experience in epidemiology, public health, health services research, health policy, economics or related fields
• Foundational knowledge of epidemiologic concepts such as observational study designs, measures of association, and common sources sources of bias and confounding
• Familiarity / competency with statistical programming tool such as R, SQL, SAS or similar platform
• Ability to work effectively both individually and as part of a team
• Detail oriented with exceptional interpersonal and time management skills
• Keen interest in learning and sharing knowledge
• Strong academic record
• Proficiency with Microsoft Office

Preferred:

• Enrolled in life sciences related advanced degree program
• Strong understanding of the scientific method; formal training in quantitative methodologies
• Familiarity with interactive data visualization tools such as R Shiny, Power BI, Tableau, or equivalent platforms
• Familiarity with working in virtual AWS environment, Git, and Github

Essential duties include but are not limited to:

Help streamline internal processes – work directly with the Precision leadership to improve processes and efficiency; investigate optimal research techniques and implementation strategies; update existing tools and documentation to increase adherence to best practices; support development and refinement of interactive tools that use existing real-world evidence analyses.

Support ongoing research projects – assist with literature reviews on diverse healthcare topics; help with real-world evidence studies including protocol development, data programming, and results; develop interactive summaries of real-world evidence analyses; help interpret and communicate quantitative and qualitative findings to internal and external audiences; contribute to reports, results tables, presentations or peer-reviewed manuscripts; participate in client-facing activities; provide administrative project support.

Qualifications:

Required:

• Enrolled in a public health (epidemiology, biostatistics, bioinformatics), economics, data science, life sciences, or healthcare related undergraduate, or preferably, graduate program at an academic institution at the time of recruitment.

Other required:

• Proven interest in public health, life sciences, or pharmaceutical research and analytics
• Research experience in epidemiology, public health, health services research, health policy, economics or related fields
• Foundational knowledge of epidemiologic concepts such as observational study designs, measures of association, and common sources sources of bias and confounding
• Familiarity / competency with statistical programming tool such as R, SQL, SAS or similar platform
• Ability to work effectively both individually and as part of a team
• Detail oriented with exceptional interpersonal and time management skills
• Keen interest in learning and sharing knowledge
• Strong academic record
• Proficiency with Microsoft Office

Preferred:

• Enrolled in life sciences related advanced degree program
• Strong understanding of the scientific method; formal training in quantitative methodologies
• Familiarity with interactive data visualization tools such as R Shiny, Power BI, Tableau, or equivalent platforms
• Familiarity with working in virtual AWS environment, Git, and Github

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen of our business decisions and to empower and scale product innovations. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, economics, and machine learning. Aligned and partnering with product groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure the impact / incrementality on our community of players, developers, and advertisers.

WHY ADVERTISING SCIENCE?

Advertising at Roblox is new, facing critical scale, effectiveness, and implementation challenges, while operating in our civility and user focused experiences. As a new strategic area, work will be innovative and impactful. Scientific rigor will be critical in success as we organize our data model, design principled measurement systems, and architect the future of incrementality measurement and actioning, to enable our communities.

In this role, you will contribute to the new Ads Science team within the broader Economy DSA team, collaborating with engineers and product managers to innovate our advertising systems and operations. Work will include data pipeline design and ownership, modeling for ad delivery and targeting, modeling for user segmentation / experimentation, and experimental design and analysis. We are early in this multi-year journey, and seek a dedicated and passionate scientist to help design this vision and execute the innovation to achieve it.

You Will:

• Design and lead offline model evaluation end-to-end (pipelines, frameworks, analysis).
• Contribute to ads ML feature and model improvements, collaborating with engineering to put these in production.
• Build offline evaluation and simulation models for our ads marketplace.
• Accelerate product development through your understanding of the underlying data and your ability to partner with product and technical leaders to provide insights.
• Lead experimental design and analysis for your ads domain.
• Design science roadmaps and experimentation agendas to determine success of product feature launches.

You Have:

• Domain experience in digital ads systems, including ownership of critical analytic or production pipelines.
• 4+ years of industry or academic experience in data science, economics, analytics, or machine learning engineering.
• Expertise in data transformation and programming, and proficiency in developing data pipelines through use of Spark, Hive, and Airflow.
• Experience with auctions and experimentation in market settings.
• Graduate education in a technical field (preferred: rigorous applied training including a graduate degree in economics, statistics, bioinformatics, cognitive science, physics, or similar).

You Are:

• Candid on relative opportunities for impact, and evidence-seeking to update beliefs.
• Passionate about Roblox’s mission to connect a billion people every day with optimism and civility, including through increasing earnings for our creator community.
• A strong communicator. You understand that analysis must be presented in meaningful ways and lead spirited discussions about the findings. You can explain technical concepts to non-technical audiences and discuss appropriate tradeoffs.
• Effective in a collaborative work environment with a track record of simplifying complex and ambiguous problems.

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Data Scientist II, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, ML) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers
• Evaluating ads system health: understanding changes and drivers of our complex systems, and diagnosing issues through a set of input/output metrics of each component.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Provide strategic thought partnership to cross-functional teams, leveraging data-driven insights to influence and guide product decisions, roadmap prioritization, and overall business strategy.
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with Product Management, Engineering stakeholders ;work effectively with cross-functional partners in a global company.
• 3+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.
• Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

Profluent is seeking a Principal Infrastructure & Security Engineer to serve as the primary owner of Profluent’s security posture across scientific systems, lab automation environments, cloud and business infrastructure, endpoints, identity systems, and core operational workflows.

This person will be accountable for the design, implementation, operation, and continuous improvement of the technical controls, security standards, and operating practices that protect Profluent’s systems and data. This includes security architecture, access controls, hardening, monitoring, incident readiness, vendor and customer security assurance, and the systems and evidence required to achieve and maintain compliance commitments.

This is not a narrow compliance-only or infrastructure-only role. It is a broad ownership role for security across Profluent’s environments, with close partnership across Operations, Machine Learning, Bioinformatics, and Lab Automation.

Responsibilities

• Own Profluent’s overall security and compliance posture across company systems, scientific computing, lab automation, endpoints, identity, SaaS, cloud infrastructure, networking, and data-handling workflows, and be accountable for the ongoing maturity of security controls and practices across those environments
• Lead the implementation and operational maturity work required for Profluent to achieve and maintain SOC 2 and related compliance certification requirements, including control operation, evidence collection, monitoring, and repeatable processes
• Serve as the primary owner for security and compliance readiness across company systems, ensuring that Profluent can meet ongoing audit, certification, and customer assurance requirements over time 
• Own the translation of customer agreements, internal policies, and compliance requirements into concrete technical and operational controls
• Standardize and harden bioinformatics, lab informatics, and machine learning environments to align with security, reliability, and compliance requirements
• Define and drive adoption of secure baseline configurations, access controls, logging, backup practices, patching standards, and change management processes
• Own and evolve how Profluent approaches security more broadly, identifying gaps, prioritizing risks, and driving improvements beyond minimum compliance scope
• Drive standardization of Windows-based lab automation environments, balancing security, uptime, vendor constraints, and usability in laboratory settings
• Collaborate with stakeholders to document controls, system boundaries, standard operating procedures, and technical evidence needed for audits, certification efforts, and customer reviews
• Support vendor and platform evaluations related to security, observability, endpoint management, and infrastructure operations
• Improve identity, access, and account lifecycle management across company systems, including onboarding, offboarding, least-privilege access, and periodic access review support 
• Monitor key systems and respond to operational issues with an emphasis on root-cause analysis and durable remediation
• Maintain asset, system, and environment documentation so that critical processes are auditable, supportable, and repeatable

Qualifications

• Experience operating with broad ownership across infrastructure, security, and compliance in regulated, audit-conscious, or security-sensitive environments
• Experience serving as the most senior or primary security owner in a startup or scaling environment, even without a large dedicated security team
• Breadth across infrastructure security, corporate security, IAM, endpoint management, logging and monitoring, vulnerability reduction, incident response, vendor risk, and compliance
• Demonstrated ability to take ownership in ambiguous environments and set direction, not just execute within a narrowly defined specialty
• Familiarity with Windows-based lab automation systems and the realities of instrument-connected or vendor-managed environments
• Experience implementing or operating against security and compliance frameworks such as SOC 2, ISO 27001, NIST CSF, or similar
• Strong understanding of identity and access management, SSO, MFA, endpoint management, logging, patching, vulnerability reduction, and system hardening
• Ability to translate compliance and contractual data-handling requirements into concrete technical and operational controls
• Strong documentation skills, with the ability to create policies, procedures, standards, and technical runbooks that others can follow
• Experience preparing organizations for, achieving, or maintaining external compliance certifications or audit readiness
• Experience with infrastructure as code and/or configuration management tools such as Terraform, Ansible, or equivalent
• Experience administering Windows environments, preferably including systems used in laboratory, automation, manufacturing, or instrument-connected settings

Preferences (but not required)

• Familiarity with audit evidence preparation, control testing, and coordination with external auditors
• Familiarity with networking fundamentals including firewalls, routing, VLANs, NAT, VPNs, and secure remote access
• Experience influencing cross-functional teams and improving organizations mature security practices without relying on rigid bureaucracy

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

The Opportunity:

Universal DX is seeking an experienced Senior Biostatistician to join our growing product development team working on the development and commercialization of Next Generation Sequencing (NGS) products for early cancer detection. This role will be instrumental in the planning, development, and execution of statistical analyses for Analytical Validation (AV) studies supporting Signal-C, Universal DX’s screening test for colorectal cancer. This role will work flexibly within a matrixed organization, collaborating across multiple teams within Product Development.

You will be part of a team that is passionate about developing novel diagnostic tests for the early detection of cancers. As part of the team, you will be in a Company that aims more than to become one of the leaders in the industry. We want to have a huge positive impact on society by achieving the ambitious purpose of “making cancer a curable disease by detecting it earlier”.

How you’ll contribute:

What you’ll bring:

What we´ll offer:

The Opportunity:

This role represents a unique opportunity to serve as a senior scientific and strategic leader within Cancer Immunology, with primary responsibility for driving the discovery and advancement of novel immuno-oncology targets and therapeutic modalities. We are seeking an accomplished leader who combines deep scientific expertise with strong people leadership to shape strategy, guide portfolio decisions, and advance high-impact discovery programs.

The successful candidate will lead a multidisciplinary team to progress innovative immuno-oncology programs from early discovery through Development Candidate nomination, while providing senior oversight of scientific integration across Discovery and Translational Cancer Immunology. This role reports to the Vice President and Head of Cancer Immunology and partners closely with Research and Development leadership to support portfolio prioritization and governance. Key aspects of the role include:

• Discovery Program Leadership & Protfolio Oversight: Provide executive-level leadership of Cancer Immunology discovery programs from project qualification through Development Candidate nomination. Drive the identification and validation of novel immuno-oncology targets, ensuring seamless progression of programs into Translational Cancer Immunology.

• Scientific Strategy & Platform Leadership: Define and evolve the scientific vision and long-term strategy for Cancer Immunology discovery. Provide senior oversight of the development and optimization of experimental platforms, including in vitro and in vivo models, phenotypic screening, and advanced assay toolkits. Champion the exploration and implementation of new therapeutic modalities, such as TCEs, ADCs, and bispecifics.

• Scientific Integration & Operational Excellence: Provide senior oversight of scientific integration across Discovery and Translational Cancer Immunology, ensuring operational rigor, platform support, and alignment of resources. Leverage enabling functions and data-driven insights to enhance experimental design, reproducibility, and program execution. Promote the development and deployment of modern data systems and analytics to advance scientific and operational excellence, enabling the establishment of a digitally empowered Cancer Immunology team within the broader organization.

• Cross-functional Collaboration: Act as a key partner to Research Leadership to support advancement of programs from early discovery into the clinical development portfolio. Foster collaboration across multidisciplinary teams to ensure that discovery efforts, platform capabilities including data platforms, and translational priorities are coordinated and integrated.

• Team Leadership & Mentorship: Lead, mentor, and inspire a multidisciplinary team of PhD and non-PhD scientists. Cultivate a culture of scientific excellence, innovation, and collaboration.

• External Engagement: Spearhead collaborations with academic partners and external organizations. Partner with key stakeholders to define publication strategies and support advancement of the company’s scientific reputation in the field.

Required Skills, Experience, and Education:

• Education & Scientific Expertise: Ph.D. in immunology, cancer biology, or a related discipline, with deep expertise in tumor immunology, immune-evasive oncogenic signaling pathways, and/or immunotherapy. Demonstrated track record of excellence in research, evidenced by high-impact publications.

• Industry Experience: 20+ years of post-PhD experience in biomedical research and oncology drug discovery, including substantial experience in biotech or pharmaceutical settings. Demonstrated leadership in oncology drug discovery and development, including experience with antibody-directed therapies such as T cell engagers, ADCs, or bispecific antibodies, is required. Experience setting early discovery strategy is highly desirable.

• Senior Leadership & Organizational Impact: Proven ability to lead complex, multidisciplinary organizations and influence across functions and levels. Demonstrated experience in portfolio decision-making, program governance, and developing scientific leaders.

• Strategic & Analytical Thinking: Enterprise-level strategic thinker capable of prioritizing initiatives, anticipating challenges, and executing effectively in a dynamic, high-energy environment. Rigorous, quantitative, and detail-oriented experimentalist.

• Collaboration & Communication: Thrives in a collaborative, interdisciplinary team setting. Excellent written and verbal communication skills, with the ability to influence and align diverse stakeholders.

Preferred Skills:

• Experience with chemistry-based therapies, including small molecules or ADC payloads.

• Familiarity with bioinformatics-driven discovery and integrating computational insights into experimental design.

• Demonstrated proficiency with modern data platforms, machine learning approaches, and advanced analytics to support Cancer Immunology research and decision-making.

• Prior experience as a Program Team Leader, with a track record of driving cross-functional strategy and execution across discovery and development stages.

 #LI-Hybrid  #LI-LN1

We’re looking for a Senior Software Engineer to help design, build, and scale Profluent’s data platform. This platform houses data from protein engineering campaigns, including protein designs, experimental results, partner datasets, analytical outputs, and model-ready training data. It enables rapid machine learning, biological discovery, and secure collaboration across internal and external programs.

This role is ideal for an engineer who enjoys building robust data systems: secure ingestion pipelines, well-structured warehouses, reliable data models, access controls, auditability, and infrastructure that makes complex scientific data usable at scale. You will work closely with ML, bioinformatics, and program teams to ensure Profluent’s data is organized, governed, accessible, and protected.

Responsibilities

• Design, build, and maintain scalable data infrastructure for protein engineering campaigns, including ingestion, transformation, validation, storage, and retrieval of large scientific datasets
• Develop secure data pipelines for internal and partner-generated data, with strong attention to access control, data siloing, provenance, auditability, and compliance with data use restrictions
• Own core components of Profluent’s data warehouse and data platform, using Python, GCP, PostgreSQL, BigQuery, and related cloud-native technologies
• Build systems that transform raw experimental, computational, and partner data into structured, reliable, analysis-ready and model-ready datasets
• Establish best practices for data modeling, metadata management, data quality checks, schema evolution, versioning, and documentation
• Collaborate with ML engineers, computational biologists, data scientists, and program stakeholders to understand data requirements and translate them into scalable technical systems
• Improve engineering quality through thoughtful system design, code review, testing, CI/CD, observability, and maintainable development workflows
• Contribute to architectural decisions for how Profluent stores, secures, organizes, and uses data across programs and partnerships

Qualifications

• 5+ years of software engineering, data engineering, or data platform experience
• Strong proficiency in Python and modern software development practices, including git, testing, code review, CI/CD, and production deployment
• Experience designing and operating production data pipelines, data warehouses, and data models at scale
• Hands-on experience with cloud platforms, preferably GCP, and technologies such as BigQuery, PostgreSQL, object storage, workflow orchestration, and containerized services
• Strong understanding of data security, access control, data partitioning or siloing, audit logging, and managing sensitive or restricted datasets
• Experience working with complex, heterogeneous datasets and building systems that make them reliable, discoverable, and usable
• Ability to work independently, make sound technical decisions, and drive projects from ambiguous requirements to production systems
• BS, MS, or PhD in Computer Science, Engineering, Data Science, Bioinformatics, or a related technical field, or equivalent practical experience

Preferences (but not required)

• Experience with scientific, biological, clinical, genomic, laboratory, or high-throughput experimental data
• Experience managing external partner, customer, or restricted-access datasets
• Familiarity with data governance, lineage, metadata systems, schema registries, or data catalogs
• Experience with research data systems, LIMS, ELNs, Benchling, or adjacent scientific platforms
• Background working with ML, data science, computational biology, or cross-disciplinary technical teams
• Interest in learning biology, gene editing, protein design, or machine learning concepts

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We’re looking for a hands-on engineering manager to lead Profluent’s Lab Informatics Platform team. This team builds the systems scientists use to design experiments, track samples, capture assay data, integrate with Benchling and lab automation, and make experimental data usable for analysis and machine learning.

The ideal candidate is both an experienced people manager and a strong technical lead. You’ll formally manage and mentor a small team while remaining deeply involved in architecture, data modeling, database design, and technical execution. You’ll work closely with wet-lab scientists, automation engineers, data scientists, and ML experts to build practical, scientist-facing tools that make complex experimental workflows scalable, traceable, and actionable.

Responsibilities 

• Lead, mentor, and grow a software engineering team focused on lab informatics systems, scientific data infrastructure, and scientist-facing applications
• Architect and deliver the roadmap for systems that support sample tracking, assay data capture, Benchling integration, lab automation, experimental metadata, and analysis workflows
• Design robust data models for protein engineering and gene editing experiments, including constructs, samples, reagents, cell systems, assay results, metadata, and experimental lineage across mammalian and bacterial workflows
• Partner closely with scientists to translate complex laboratory requirements into scalable software solutions that accelerate Profluent’s design-build-test-learn cycle
• Build and maintain backend systems, APIs, databases, data pipelines, and web applications using technologies such as Python, Django, PostgreSQL, BigQuery, GCP, and modern development workflows
• Establish strong engineering practices across architecture, code review, testing, CI/CD, documentation, and agile delivery

Qualifications 

• 7+ years of software engineering experience, including at least 2 years managing or leading engineers
• BS, MS, or PhD in Computer Science, Bioinformatics, Computational Biology, Engineering, or a related field, or equivalent experience
• Strong technical leadership skills, with a track record of architecting and delivering production-quality software systems
• Proficiency with Python, backend development, databases, APIs, and modern software engineering workflows
• Experience building lab informatics systems, scientific data platforms, LIMS/ELN integrations, research software, or scientist-facing applications
• Experience with data modeling and database design for complex scientific, operational, or experimental workflows
• Demonstrated ability to work closely with scientists and translate ambiguous laboratory workflows into reliable software systems

Preferences (but not required)

• Experience with Benchling, lab automation, instrument data ingestion, sample tracking, or high-throughput experimental data
• Experience with data generated from mammalian or bacterial cell systems, gene editing, protein engineering, or related biological workflows
• Frontend web development experience and interest in building intuitive scientist-facing user interfaces

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

About the Role:

Stylus Medicine is seeking an intellectually curious and creative Director, who will serve as a key scientific leader on our Platform team, owning the computational strategy that drives large serine recombinase (LSR) engineering and clinical translation. This role sits at the intersection of protein engineering, multi-omics analysis, and AI/ML-driven design and will lead a high-impact team spanning NGS and computational biology while driving the analytical infrastructure and predictive capabilities needed to advance our proprietary LSR platform from discovery through translation.

Key Responsibilities & Accountabilities:

• Lead and develop a team of NGS and computational biology scientists, setting technical direction, mentoring team members, and fostering a collaborative, high-performance culture
• Lead computational efforts to design and optimize LSRs and related genome engineering proteins for genetic medicine applications, integrating sequence-function, structure-function, and protein-DNA interaction datasets to guide engineering campaigns
• Lead analysis of NGS data from LSR experiments — including amplicon sequencing, WGS, hybrid capture, and long-read sequencing — to quantify on-target efficiency and genome-wide specificity
• Build, apply, and critically evaluate predictive and generative models for protein variant and library design — including rigorous benchmarking of AI/ML approaches such as protein language models, structure prediction tools, and generative design frameworks
• Integrate proprietary screening data with public evolutionary and structural datasets to prioritize variants and identify engineering levers for activity, specificity, and developability
• Oversee the design, implementation, and deployment of robust, scalable computational pipelines for multi-omics data analysis, ensuring accuracy, reproducibility, and maintainability
• Provide scientific input into platform strategy, translating computational insights into actionable directions for the broader team
• Partner closely with the Screening, Genome Engineering, and NGS teams to design experiments, interpret complex datasets, and refine engineering hypotheses
• Contribute to patent filings, regulatory submissions, and publications

Qualifications & Skills:

• PhD in Computational Biology, Bioinformatics, Protein Engineering, Machine Learning or a related quantitative discipline, with 10+ years or Master’s with 14+ years of industry experience
• Demonstrated research in protein modeling, protein design, or computational biology through publications, preprints, or equivalent industry contributions
• Hands-on experience applying AI/ML methods to protein variant and library design, including protein language models, structure prediction, and generative design approaches (e.g., AlphaFold2/3, RFdiffusion, ProteinMPNN, ESM)
• Expert-level proficiency in Python and/or R, with deep familiarity with data science libraries (e.g., Pandas, NumPy, Bioconductor, SciPy, PyTorch, or JAX)
• Experience with cloud computing platforms and workflow management systems
• Excellent communication and documentation skills, with a track record of effective collaboration in fast-paced, interdisciplinary environments

Pay Range; $245,000 - $265,000

The Opportunity:

We are seeking a Principal Machine Learning Scientist to lead the development of advanced machine learning approaches that accelerate small-molecule drug discovery. This role sits at the intersection of data science, chemistry, and biology, transforming complex scientific datasets into predictive models that guide target discovery, compound design, and translational hypotheses.

Working closely with experimental scientists, the Principal ML Scientist will develop cutting-edge modeling approaches that integrate chemical, biological, and phenotypic data. The successful candidate will play a key role in advancing a data-driven discovery strategy by designing predictive models, deploying innovative algorithms, and translating insights into actionable decisions that improve the speed and success of the discovery of medicines for patients with RAS-driven cancers.

Key responsibilities include:

Scientific Leadership:

• Define and lead machine learning strategies that accelerate early-stage drug discovery.

• Identify opportunities where AI and advanced analytics can meaningfully improve scientific decision-making.

• Drive the adoption of innovative modeling approaches within multidisciplinary discovery teams.

Model Development:

• Develop predictive models for:

  • Compound activity, selectivity, ADME/Tox, and developability properties.

  • Target engagement, mechanism-of-action, and phenotypic datasets.

Apply modern ML techniques such as:

• Graph neural networks.

• Deep learning for molecular representation.

• Generative chemistry models.

• Active learning frameworks for experimental design.

Cross-Functional Collaboration:

• Partner with medicinal chemists to guide compound design and optimization.

• Work with biologists to interpret complex experimental datasets and generate mechanistic hypotheses.

• Collaborate with data scientists and engineers and ML engineers to deploy models into scalable discovery workflows.

Data Integration:

• Integrate heterogeneous datasets including:

• Chemical structure and screening data.

• Imaging and phenotypic screening data.

• Structural biology and molecular simulation outputs.

Required Skills, Experience and Education:

• PhD in machine learning, computational chemistry, computational biology, computer science, or a related quantitative discipline.

• 8+ years experience applying machine learning or advanced analytics to scientific problems.

• Demonstrated experience working with chemical or biological datasets in drug discovery or related domains.

• Strong expertise in:

  • Python-based ML ecosystems (PyTorch, TensorFlow, scikit-learn).

  • Data analysis and scientific computing (NumPy, Pandas).

  • Deep learning and representation learning techniques.

• Strong understanding of early-stage drug discovery workflows.

• Ability to translate biological or chemical questions into computational frameworks and predictive models.

• Proven ability to communicate complex computational insights to.

• Passion for scientific innovation and a relentless commitment to improving patient outcomes.

Preferred Skills:

• Proven track record of applying advanced AI/ML approaches (deep learning, generative modeling, structure-based ML) to drug discovery or related life sciences domains.

• Experience with cheminformatics or bioinformatics toolkits is highly desirable.

• Familiarity with cloud computing and scalable ML workflows is a plus

• Ability to work at the interface of computational and experimental science. 

  #LI-Hybrid  #LI-LN1

The Opportunity:

As an Executive Director and Head of Research Computational Biology within our Biology Function, the individual will oversee the scientific and strategic direction of systems biology research and preclinical computational biology initiatives. The individual will lead a team of computational biologists and bioinformaticians focused on acquisition, organization, and analysis of large multi-omics data sets, using both public and proprietary data sources, that will help inform treatment strategies and guide patient stratification for a growing pipeline of RAS(ON) and targeted oncology therapeutics. We are looking for an experienced leader with strong interpersonal skills and an ability to lead a strong and diverse computational biology team. Key aspects of the role include:

• Strategic vision and leadership: Develop and implement a long-term strategy for research systems biology and bioinformatic activities to support a growing pipeline of RAS(ON) and novel targeted inhibitors. Lead and supervise a team of experienced computational biologists and bioinformaticians to generate, organize, and interpret large data sets to inform therapeutic and combination strategies for patients with cancer.

• Cross-functional collaboration across research, translational, development and medical affairs groups: Work across functions to support advancement of programs from early discovery into clinical development using biological insights derived from computational approaches. Additionally, leverage clinical data from RVMD investigational agents to generate proprietary insights into RAS mutant tumor biology and RVMD RAS(ON) inhibitor mechanisms of action.

• Technical leadership and innovation: Lead a team analyzing large, high-dimensional datasets. Work with colleagues in Information Sciences and Information Systems to oversee data integration, analysis and visualization using cloud-based platforms (AWS, Azure, GCP). Direct the development and application of cutting-edge statistical analysis, AI/ML methods, generative AI models, and MLOps principles to elucidate findings and generate new insights related to biomarker discovery, drug target identification, and predictive modeling. Establish and implement modern workflow management systems (Snakemake, Nextflow) and reproducible research practices.

• External collaboration: Cultivate and manage academic and industry collaborations, including CRO partnerships. Represent the company at scientific conferences through presentations and thought leadership. Maintain an active publication record in high-impact, peer reviewed journals. Drive intellectual property strategy and patent filings related to computational discoveries.

Required Skills, Experience and Education:

• Education: A Ph.D. in systems biology, computational biology, bioinformatics, or a related biological or biomedical discipline.

• Experience: Minimum of 15+ years total experience with significant pharmaceutical/biotechnology industry and management experience.

• Scientific knowledge: Deep expertise in systems biology, computational biology, and bioinformatics, including proficiency with multi-omics data integration, modeling, and analysis. Experience with single-cell technologies, spatial transcriptomics, proteomics, and epigenomics. Oncology research experience preferred but not required.

• Technical: Advanced programming skills in R, Python, and at least one additional language (Perl, C/C++, Java). Proficiency with high-performance computing (HPC) and cloud platforms (AWS, Azure, or GCP). Knowledge of workflow management tools and version control systems. Understanding of MLOps principles, model deployment, and generative AI applications in drug discovery.

• Leadership and management: Demonstrated ability to lead, mentor, and inspire interdisciplinary teams while fostering a collaborative culture. Experience managing budgets and strategic planning at the department level. Proven track record of advancing research programs from discovery through development.

• Strategic thinking: Proven strategic thinker who can align research and drug development objectives and leverage innovative technologies effectively.

• Communication: Excellent communication and presentation skills for interacting with technical teams, senior leadership, and external partners. #LI-Hybrid  #LI-GL1

The Opportunity:

The Translational Sciences Intern will support the Translational Sciences team in advancing programs that connect preclinical discovery with clinical development. This role provides exposure to how Translational Research integrates molecular biology, pharmacology, biomarker discovery, and clinical data to inform therapeutic development in precision oncology. The intern will gain insight into how translational strategies are developed to understand drug mechanisms, identify biomarkers of response and resistance, and guide clinical trial design. This position is ideal for a student interested in translational cancer research and the interface between laboratory science and clinical application. The role focuses on learning, analysis, and cross-functional collaboration within a multidisciplinary drug development environment.

This role provides the opportunity to learn some or all the following, depending on project assignments and team needs.

• How translational research supports the development of targeted therapies in oncology.

• How biomarker strategies are developed to support clinical trials and precision medicine approaches. • How preclinical data are integrated with clinical observations to understand mechanisms of response and resistance.

• How cross-functional teams across discovery biology, pharmacology, clinical development, and bioinformatics collaborate in drug development.

• How experimental and clinical datasets are analyzed and interpreted to generate translational insights.

• How translational scientists communicate complex scientific findings to multidisciplinary teams.

Required Skills, Experience and Education:

• Strong analytical, critical-thinking, and problem-solving skills.

• Ability to interpret scientific literature and synthesize complex scientific information.

• Strong written and verbal communication skills.

• Interest in oncology, molecular biology, or translational research.

• Organized, detail-oriented, and able to work independently with guidance.

• Professional curiosity and willingness to learn new concepts.

• Pursuing a bachelor’s or master’s degree in a STEM field (e.g., biology, biochemistry, molecular biology, biomedical engineering, or related discipline).

Preferred Skills:

• Coursework or research experience in cancer biology, molecular biology, or pharmacology.

• Familiarity with biomarker concepts or translational research approaches.

• Experience with basic laboratory techniques or biological data analysis.

• Experience preparing scientific presentations or summarizing research findings.

• Interest in precision medicine and targeted cancer therapies. 

  #LI-Hybrid  #LI-AP1

The Opportunity:

As a Director, Molecular Pathology, you will be a key member of a cross-functional Translational Sciences Team, reporting to the Senior Director and Head of Translational Sciences within Translational Research and will:

• Biomarker Strategy: Define and execute molecular and digital pathology-driven biomarker strategies.

• Integration of Advanced Modalities: Lead adoption of molecular pathology and spatial technologies (to support translational research and broader BDR needs.

• Digital & Computational Pathology: Drive implementation of whole-slide imaging, AI/ML-based image analysis, and integration of spatial biomarker analytics into decision-making.

• Data Interpretation & Reporting: Provide expert interpretation of pathology data, ensuring robust correlation with clinical outcomes and mechanistic insights.

• Cross-functional Leadership: Collaborate with Translational Medicine, Bioinformatics, and Clinical Development colleagues to implement candidate biomarkers into Translational Biomarker plans for RAS(ON) inhibitors in alignment with overarching clinical development strategies.

Responsibilities

• Scientific Leadership & Execution: Perform and interpret multiplex spatial biomarker datasets to inform Translational hypotheses and clinical strategies. Establish QC standards for data acquisition and analysis.

• Cross-Functional Collaboration: Partner within Research and Clinical teams to integrate spatial biomarker findings into translational plans. Collaborate with Systems Biology and Information Sciences teams to enable visualization tools

• External Partnership Management: Serve as primary scientific liaison to CROs for spatial biomarker workflows; review deliverables, troubleshoot issues, and drive continuous improvement.

• Capability Building: Document best practices and SOPs for spatial biomarker workflows; recommend platform upgrades and pilot evaluations.

Required Skills, Experience & Education:

• 10+ years in digital pathology/spatial biology within pharma, biotech, or CRO settings.

• Scientific Expertise: Deep knowledge of spatial biology (e.g. spatial transcriptomics, Visium, Xenium, GeoMx, MerFish, etc.); ability to translate complex data into actionable insights

• Execution Excellence: Bias for action; delivers high-quality analyses under tight timelines

• Collaboration & Influence: Builds strong relationships across functions and with external partners; communicates clearly and persuasively.

• Innovation & Continuous Improvement: Identifies opportunities to enhance workflows and adopt emerging technologies.

• PhD/MD or equivalent in Cancer Biology, Translational Sciences, Pathology or related discipline.

Preferred Skills:

• Hands-on experience with spatial pathology workloads.

• Familiarity with AI/ML-assisted pathology workflows and spatial statistics.

• Proven ability to manage CRO relationships and deliver time-sensitive biomarker analyses.

#LI-Hybrid  #LI-LN1

We're looking for a Protein Design Scientist to own the development and deployment of agentic workflows for protein design. In this role, you will build systems that orchestrate protein language models, structure predictors, fitness scoring tools, and experimental feedback into automated or semi-automated design pipelines - closing the loop between computation and the wet lab.

This is a hands-on, high-ownership role. You'll work across the full stack of a design workflow: selecting and integrating models, defining agent logic and iteration strategies, building robust infrastructure for deployment, and collaborating closely with ML scientists, protein design scientists, and biologists to ensure your systems produce experimentally actionable results.

As an early employee, you will shape how Profluent approaches workflow automation and help define best practices for agentic systems in protein engineering.

Responsibilities

• Design, build, and deploy end-to-end agentic workflows that take protein function specifications and produce ranked candidate sequences for experimental validation
• Integrate protein language models, structure prediction tools, and scoring functions into multi-step pipelines with iteration, feedback loops, and human-in-the-loop checkpoints
• Own the full lifecycle of workflow systems: architecture, implementation, testing, deployment, monitoring, and iteration based on experimental outcomes
• Collaborate with ML scientists to evaluate and integrate new models into workflows, and with protein design scientists and biologists to translate scientific goals into computational specifications and ensure workflows align with experimental realities
• Develop tooling for experiment tracking, logging, reproducibility, and versioning of design campaigns
• Evaluate and benchmark workflow performance against experimental results, using outcomes to improve agent strategies and model selection
• Partner with ML scientists to identify where existing models fall short in agentic contexts and inform priorities for model development, fine-tuning, and evaluation

Qualifications

• PhD (or equivalent industry experience) in Computational Biology, Bioinformatics, Computer Science, Machine Learning, Biochemistry, or a related field
• Minimum of 3+ years of experience as a protein design scientist
• Strong software engineering skills: you write clean, modular, production-quality code (Python required; experience with workflow orchestration frameworks is a plus)
• Hands-on experience with protein language models (e.g., ESM, ProGen, ProtTrans) for sequence generation, scoring, or representation
• Demonstrated understanding of protein engineering principles: structure-function relationships, fitness landscapes, and how computational predictions connect to wet-lab validation
• Experience building multi-component systems that chain model inference with data processing, filtering, and decision logic

Preferences (but not required)

• Experience with agentic AI systems, LLM tool-use patterns, or multi-step reasoning pipelines
• Familiarity with structure prediction tools (AlphaFold, RoseTTAFold, ESMFold) and inverse folding methods (ProteinMPNN, LigandMPNN)
• Track record of computational designs that were experimentally validated
• Experience with cloud compute platforms (GCP, AWS, Azure) and containerized deployment (Docker, Kubernetes)
• Publications in protein design, protein engineering, or ML for biology at major conferences or journals
• Familiarity with directed evolution, rational design, or de novo protein design strategies

What We Offer 

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We are seeking an energetic, highly organized, and adaptable Operations Associate I/II to serve as the backbone of our office and laboratory environment. This is a dynamic role where you will manage the daily pulse of our workspace while supporting our technical teams in facility expansion and lab maintenance.

The ideal candidate thrives in a startup atmosphere - moving seamlessly from coordinating a team social to assisting with lab safety protocols or assembling furniture for the office.

Responsibilities

Primary Operations & Office Management 

• Act as the primary stakeholder for reception, greeting and managing all incoming vendors, visitors, and deliveries
• Oversee all shipping/receiving, mail sorting, and courier pickups
• Maintain a high standard for the pantry, fridge, and stationery stock; ensure general kitchen and office cleanliness
• Manage room bookings, food orders for meetings, and desk/office setups for new hires; fulfill other administrative responsibilities assigned as needed
• Assist in planning and executing monthly team activities and quarterly off-site vendor visits
• Lead purchasing for office supplies, IT equipment, and social events

Lab & Facility Support

• Assist the Lab and Operations Manager in setting up new office and lab spaces, including furniture assembly and equipment placement
• Support the wet lab through inventory management, specialized waste management, and routine equipment maintenance
• Maintain in-depth knowledge of safety/emergency protocols; ensure the site remains compliant and safe for all staff
• Act as a buyer for the Bioinformatics, Machine Learning, and Biology teams, managing Purchase Orders (POs) and maintaining current vendor information
• Assist with account reconciliation and maintaining up-to-date vendor records
• Fulfill additional support on projects assigned as needed

Qualifications

• BA or BS or AA/AS +2 years relevant work experience
• Must be able to lift at least 25 lbs
• Previous experience managing Purchase Orders (POs) 
• Previous customer service experience or prior public-facing roles
• Exceptional interpersonal communication, excellent customer-facing skills, elite time management, and a high degree of organizational efficiency
• Ability to be adaptable/flexible in the day-to-day

Preferences (but not required)

• BS in STEM  
• 1+ years of experience in a wet lab environment
• Familiarity with BSL2 safety standards and hazardous waste protocols
• Proficiency with Rippling, Ramp, Google Drive, and Notion
• Ability to lift 40 lbs
• Desire to learn new skills and initiate and own new tasks or projects 

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into new technologies for biomolecular design. This position offers an opportunity to work at the forefront of generative modeling research across language processing, representation learning, and protein engineering. You should be a self-directed researcher who has the ability to rapidly prototype and evaluate new models and algorithms in the biomolecular domain. 

As an early employee, you will proactively shape the direction of our machine learning efforts and collaborate across diverse teams of computational and experimental scientists.

Responsibilities

• Design and develop state-of-the-art deep learning methods for protein sequence, structure, and function prediction and apply them to protein design
• Curate relevant datasets and design tasks for rigorous evaluation of generative models 
• Collaborate with Biology team to design and characterize novel designed biomolecules
• Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings
• Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company

Qualifications

• PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field
• Experience with conceiving of, implementing, and evaluating novel machine learning techniques
• Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)
• Experience with modern deep learning frameworks such as Pytorch or Jax

Preferences (but not required)

• Familiarity with foundational biology of proteins and nucleic acids
• Experience developing machine learning models for proteins (language models, structure prediction, design)
• Previous experience in data extraction and curation from bioinformatics data sources
• Familiarity with wet lab experimental assays and associated limitations
• Experience with cloud compute platforms (GCP, AWS, Azure)

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We’re seeking an experienced computational scientist to lead the design, development, and operation of the NGS analysis platform that powers Profluent’s gene editing and protein design programs. You’ll work at the intersection of computational biology, software engineering, and experimental biology to build scalable systems that extract clear, actionable insights from large-scale sequencing data.

In this role, you’ll architect core bioinformatics infrastructure, define analytical strategy, and collaborate closely with experimental and ML teams to accelerate design-build-test-learn cycles. You’ll also mentor team members, promote software engineering best practices, and help shape the future of Profluent’s computational biology capabilities.

Responsibilities 

• Lead design and implementation of scalable NGS analysis pipelines supporting gene editing and protein engineering workflows
• Develop clear, intuitive visualizations and reports to communicate sequencing results and biological insights
• Manage cloud-based compute environments and data systems for large-scale datasets
• Partner with biology teams to analyze results, troubleshoot, and optimize experimental design
• Collaborate with machine learning teams to curate data for model training
• Establish best practices for code review, testing, and CI/CD in computational workflows
• Mentor junior scientists and foster a culture of rigor, reproducibility, and innovation

Qualifications

• PhD or MS in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field
• 5+ years of experience analyzing NGS datasets (e.g., amplicon sequencing, high-throughput editing, or screening experiments)
• Strong programming skills in Python (pandas, numpy, biopython, etc.)
• Expertise with workflow orchestration tools (Nextflow, Snakemake) and cloud environments (GCP, AWS)
• Experience with containerization (Docker, Kubernetes) and scalable compute infrastructure
• Deep understanding of Linux, git-based version control, and software engineering best practices
• Proven ability to transform complex sequencing data into actionable biological insights

Preferences (but not required)

• Experience with gene editing technologies (CRISPR, base or prime editing; strongly preferred)
• Familiarity with SQL and data modeling for biological or experimental data
• Experience with LIMS platforms (e.g., Benchling) and lab data integration
• Track record of developing production-quality scientific software or open-source bioinformatics tools

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

Please note that this position can be based in San Diego, CA OR San Francisco, CA OR Princeton, NJ. Acadia's hybrid model requires this role to work in our office three days per week on average.

Position Summary

The Executive Director will lead the design and implementation of disease and drug mechanism of action (MoA) studies to advance therapeutics into and through clinical development. The position requires deep experience in translational sciences, proven leadership and mentoring skills, hands-on rare disease experience, strong understanding of clinical biomarker development, and a deep understanding of drug development from discovery through late-stage clinical studies.  The ability to synthesize complex biological concepts and data into clearly communicated actionable insights is critical, as is a track record of successful partnering with functions across the drug development paradigm. 

Primary Responsibilities

• Develop translational biology strategies to interrogate disease and drug MoA, implement and drive execution for candidate targets and therapeutics

• Lead nonclinical sciences function, mentor scientists across translational sciences

• Partners with colleagues across the drug development paradigm to develop and test hypotheses designed to advance target and candidate molecule evaluation through various stages of development

• Partner with Translational Science colleagues to develop preclinical strategies supporting indication selection, PK/PD analyses, and mechanistic development for successful IND filing and clinical development

• Synthesize, analyze and integrate complex biological data, providing clear and actionable insights to drive drug development decisions

• Identify, evaluate and leverage cutting-edge technologies to expedite early-stage program development & success

• Identify and manage CROs and build strong collaborative relationships with Acadia partners to maximize the application of complementary areas of expertise

• Present programs and data for asset team, governance and senior / executive management review

• Contribute, as author and strategist, to document generation for preclinical studies & clinical protocols, clinical study reports, statistical analysis plans, research partnerships, regulatory materials (IB, IND, NDA, etc.) and publications

• Perform other responsibilities as assigned

Education/Experience/Skills

PhD in life science or related field.  Targeting 15 years of progressively responsible experience in drug development within the pharmaceutical or biotech industry.  An equivalent combination of relevant education and experience may be considered.

Key Skills:

• Strong cross-functional leadership with a proven ability to build collaborative, high-performing teams and represent nonclinical sciences across Translational Sciences and program teams
  
  
• Hands-on experience across drug discovery, preclinical development, and clinical-stage programs (Phase 1–3), including rare disease
  
  
• Demonstrated success leading programs through IND filing, with deep expertise in small molecule INDs and regulatory submissions (IND, NDA, BLA)
  
  
• Expertise in preclinical  (MoA) analysis, indication selection, and supporting clinical development strategies
  
  
• Strong understanding of clinical biomarker strategy and development
  
  
• Ability to analyze complex, multifactorial datasets, with computational literacy and collaboration with computational biology; bioinformatics integration experience is a plus
  
  
• Effective communicator with high emotional intelligence; skilled in presenting complex data to senior leadership and influencing stakeholders
  
  
• Proven ability to make decisions under uncertainty, aligning with timelines and organizational objectives
  
  
• Track record of driving performance through goal-setting, accountability, continuous improvement, and leading change across teams
  
  
• Able to manage multiple priorities in fast-paced environments, with flexibility for domestic and international travel; experience in neurology and across modalities (e.g., ASO, mRNA) is a plus

Physical Requirements

This role involves regular standing, walking, sitting, and the use of hands for handling or operating equipment. The employee may also need to reach, climb, balance, stoop, kneel, crouch, and maintain visual, verbal, and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds.  This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.

LI #SL-1

The Opportunity:

Universal DX is seeking an IVD Scientist I to join our growing Product Development team working on the development and commercialization of Next Generation Sequencing (NGS) products for early cancer detection. This role will support the planning, execution, and documentation of analytical validation (AV) studies to characterize the performance of Universal DX’s screening test for colorectal cancer.

This is an individual contributor scientist role intended for candidates early in their regulated IVD career. Candidates with substantially more IVD development experience than this role requires may be a better fit for our Senior IVD Scientist opening.

This role may be performed remotely (US) with regular cross-functional engagement, or on-site in the lab as needed.

How You'll Contribute:

· Draft and review technical documents, including protocols, reports, and standard operating procedures (SOPs).

· Support development and analytical validation (AV) / verification studies in alignment with regulatory standards and internal procedures (e.g., assist with precision, LoB/LoD, linearity, interference, robustness studies, as applicable).

· Execute study activities in the lab and/or coordinate study execution with internal partners and vendors; ensure accurate data capture and traceability.

· Coordinate the execution and analysis of studies with the lab and biostatistics teams.

· Identify and communicate technical challenges in assay workflow and assist with investigations and corrective actions under guidance.

· Collaborate with R&D teams to translate research findings into scalable diagnostic assay workflows suitable for AV and regulated use.

· Partner with Automation, R&D, Quality Assurance (QA), and Regulatory Affairs (RA) teams to meet project deadlines.

· Contribute to cross-functional meetings, presenting progress and technical updates.

· Maintain adherence to quality management systems (QMS) and ensure compliance with regulatory guidelines.

What you’ll bring:

Required Qualifications

· Ph.D. in Molecular Biology, Biochemistry, Genetics, Bioengineering, or a related field.

· Experience with molecular biology and NGS (academic and/or industry).

· Demonstrated ability to learn and apply structured study execution practices; comfort working from protocols and documenting work clearly.

· Strong writing skills and experience with documentation (e.g., protocols, reports, lab records).

· Proficiency in the interpretation and documentation of study results.

· Proven ability to collaborate effectively with cross-functional teams.

· Excellent problem-solving, analytical, and organizational skills.

· Comfortable working in a fast-paced environment with ability to adapt to shifting priorities.

· Working knowledge of regulatory requirements and industry standards relevant to IVD development (e.g., FDA expectations and CLSI guideline concepts). (Support-level; not expected to have led a PMA.)

Preferred Qualifications

· Internship or industry experience supporting IVD analytical validation studies or design-control documentation.

· Experience with cfDNA methylation sequencing and/or liquid biopsy technologies.

· Familiarity with regulated documentation practices (traceability, controlled documents, deviation documentation).

What we´ll offer:

· 22 days of PTO with the possibility to carry over 10 days to the following year.

· Company Holidays, plus your Birthday off!

· Company-sponsored benefit plans, including medical, dental, and vision insurance plus life, STD, and LTD coverage, and 401(k).

· Flexible work schedule

· And more to come!

Our generative models learn the blueprint of life by modeling large-scale evolutionary data, enabling us to engineer and write biology in unprecedented ways. We are seeking a passionate Computational Research Intern to join moonshot projects at the intersection of bioinformatics and machine learning.

This is a rare opportunity to tackle open-ended scientific and engineering challenges with direct potential for high-impact publications and real-world applications in synthetic biology and protein engineering.

Responsibilities

• Design and implement computational approaches to advance cutting-edge research in bioinformatics and machine learning
• Analyze large-scale genomic and protein datasets to uncover new biological insights and capabilities
• Collaborate closely with scientists and engineers across machine learning, protein engineering, and biology teams
• Document and present research findings internally, with the potential to publish in leading journals and conferences

Qualifications 

• Enrolled in a BS, MS, or PhD program in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field
• Strong programming skills in Python and familiarity with scientific computing libraries (e.g., NumPy, pandas, Jupyter)
• Experience in one or more of the following: machine learning, large-scale data analysis, genomics, or protein bioinformatics
• Excellent problem-solving skills, scientific curiosity, and ability to work both independently and collaboratively

Internship Details

• Typical duration: 12 weeks, with flexible start dates
• Hybrid: 2 - 3 days on-site per week in our Emeryville, CA headquarters
• Salary: $1,667 per week
• Opportunity to publish your work and make a lasting impact in computational biology and AI-driven protein design

What We Offer

• Work on moonshot projects at the frontier of AI and biology
• Mentorship from leading experts in bioinformatics, machine learning, and synthetic biology
• A dynamic, mission-driven environment with the resources of a fast-growing, well-funded startup
• Competitive internship compensation and benefits

The Opportunity:

As Technical Writer, you will be responsible for the preparation and management of all regulatory documents associated with the federal submission of Signal-C throughout life cycle. Reporting to the VP of regulatory affairs, the technical reviewer/writer will play a critical role in supporting the PMA submission process for our Class III diagnostic device focused on CRC screening. This position involves creating, editing, and managing technical documentation to meet FDA regulatory requirements, including detailed reports on device design, clinical data, risk analysis, and manufacturing processes. The ideal candidate is detail-oriented, experienced in medical device regulations, and adept at translating complex scientific information into precise, accessible content.

You will be part of a team that is passionate about developing novel diagnostic tests for the early detection of cancers. As part of the team, you will be in a Company that aims more than to become one of the leaders in the industry. We want to have a huge positive impact on society by achieving the ambitious purpose of “making cancer a curable disease by detecting it earlier”.

How you’ll contribute:

Role Description:

We are seeking a dynamic Project Manager to lead customer-facing mRNA and lipid nanoparticle (LNP) projects, with a primary focus on LNP development and delivery. You will be responsible for ensuring all project deliverables are executed on time, within scope, and aligned with client expectations.

The ideal candidate brings a solid scientific foundation, exceptional communication skills, sharp problem-solving abilities, and strong business acumen. You’ll serve as the key liaison between external clients and internal cross-functional teams — from R&D to manufacturing — requiring agility, diplomacy, and a results-driven mindset. Success in this role demands someone who thrives in GenScript’s fast-paced, collaborative, and high-performance culture.

Key Responsibilities:

• Partner with Commercial and Production teams to ensure seamless project execution and customer satisfaction.
• Capture detailed project requirements, clarify specifications, and align expectations with clients.
• Develop and communicate customized project plans to clients and internal stakeholders.
• Monitor order production progress, evaluate performance metrics, and implement process improvements.
• Provide scientific troubleshooting for unexpected results and propose data-driven solutions.
• Deliver timely project updates to clients via email/telecom, adhering to agreed milestones.
• Lead cross-functional coordination across all project phases (initiation to closure).
• Address client complaints or quality concerns, collaborating with Production to resolve issues.
• Maintain comprehensive project documentation (reports, records, and compliance files).
• Support Production in analyzing and expanding service offerings for the US market.
• Serve as an R&D consultant, translating client needs into actionable research plans.
• Represent the company at customer visits and scientific events (conferences, workshops).
• Fulfill additional tasks assigned by Project Leaders, upholding service excellence.

Qualifications:

• Master’s degree or higher in Chemical Engineering, Pharmaceutical Sciences, or a related field.
• Strong technical foundation in RNA biology and lipid nanoparticle (LNP) formulation, with hands-on laboratory or process development experience.
• Prior project management experience preferred — demonstrated success in coordinating cross-functional teams to deliver projects on time, within scope, and on budget.
• Direct research or development experience with mRNA and LNP platforms is a strong plus.
• Customer-centric mindset with excellent interpersonal and client-facing communication skills — both written and verbal.
• Proficient in Microsoft Office Suite and familiar with common bioinformatics or lab data management tools.
• Highly organized with strong analytical, prioritization, and time management skills.
• Proven ability to juggle multiple projects simultaneously without compromising quality or deadlines.
• Resilient under pressure — thrives in fast-paced, high-stakes environments.

Benefit:

• Medical Insurance/ Vision Insurance/ Dental Insurance
• 401(k) & Retirement Savings Plan (RSP)
• Short Term Disability Insurance
• New Child Leave
• Paid Time Off
• Paid Company Holidays per year
• Paid Sick Days (earned based on hours worked)
• Compassionate Leave
• Jury Duty Leave
• Float day
• Personal days

Perks: 

• Free colleague meals during shift
• Onsite massages Charis
• Onsite gyms

Compensation:
Salary range: $70,000 – $85,000 total compensation, including bonus, depending on experience and qualifications.

POSITION SUMMARY:

We are seeking a product leader to drive the development of oncology diagnostic algorithms and data products powered by next-generation sequencing and large-scale clinico-genomic datasets.

This role will focus on identifying high-value product opportunities and leading the development of algorithm-driven solutions that support cancer detection, disease monitoring, biomarker discovery, and drug development.

The ideal candidate brings strong product management experience in oncology diagnostics or genomics, with the ability to translate complex scientific and data capabilities into clinically meaningful and commercially successful products.

This leader will work closely with bioinformatics, data science, clinical, and commercial teams to guide products from concept through validation and commercialization, helping expand Natera’s impact across precision oncology and biopharma partnerships.

KEY RESPONSIBILITIES: 

1. Define oncology algorithm product strategy
Identify and prioritize opportunities to develop algorithm-driven diagnostics and data products that address unmet needs in oncology care and drug development

2. Lead development of diagnostic algorithms and data products
Partner with bioinformatics and data science teams to translate genomic and clinical datasets into clinically meaningful algorithms supporting:

• MRD detection and monitoring
• therapy response prediction
• biomarker development
• clinical trial applications

3. Drive product lifecycle management
Lead cross-functional teams through concept development, validation strategy, launch planning, and ongoing product optimization

QUALIFICATIONS:

• 5+ years of product management experience, preferably in oncology diagnostics, genomics, or life sciences
• Demonstrated experience leading products from concept through launch and on-market management
• Strong understanding of oncology diagnostics, biomarker development, or genomic testing workflows
• Experience working with large genomic, clinical, or real-world datasets to inform product development
• Experience partnering with data science or bioinformatics teams to develop algorithm-driven products

WHAT WE’RE LOOKING FOR: 

• Strategic thinker with strong understanding of oncology diagnostics, genomic data, and algorithm-driven products
• Executive presence with the ability to engage credibly with biopharma and academic key opinion leaders
• Builder mindset — comfortable shaping new categories in AI-enabled precision oncology
• Collaborative leader who can align scientific rigor with commercial impact

COMPANY

Octant is pioneering a new generation of precision medicines by combining synthetic biology, chemistry, and AI/ML to tackle complex cellular mechanisms driving human disease. We are a small molecule therapeutics company scaling drug discovery to unlock therapies for genetically defined and historically intractable diseases.

JOB DESCRIPTION

We're looking for a computational drug discovery intern to join Octant this summer in a program funded by the Gates Foundation to identify small-molecule drugs targeting HPV-driven cancers. In this role, you'll work alongside our computational and experimental teams to build and iterate on machine learning models, explore molecular representations and structure-activity relationships, and help drive compound design and prioritization from data to decision.

THIS INTERNSHIP MIGHT BE GREAT FOR YOU IF YOU ARE/HAVE:

• Currently enrolled in or recently completed a BS or MS in a quantitative field (CS, bioinformatics, applied math, data science, computational biology, or adjacent)
• Proficient in Python for data analysis and scripting (pandas, numpy, scikit-learn at minimum)
• Experience building or training ML models on real datasets, not just coursework exercises
• At least one substantive research experience (academic lab, industry internship, or independent project) where you drove a project from question to result
• Familiarity with version control (git) and working in shared codebases
• Coursework or research exposure in at least one biological science area
• Ability to communicate results to both computational and experimental audiences
• Comfort with ambiguity and fast iteration. The project work is on a weekly cadence, which means making judgment calls with incomplete data, not waiting for perfect information

EVEN BETTER IF YOU HAVE:

• Hands-on experience with molecular representations (SMILES, fingerprints) or cheminformatics toolkits (RDKit, DeepChem)
• Experience with cloud/distributed compute environments (Databricks, Spark, or similar)
• Understanding of structure-activity relationships, compound libraries, or hit expansion concepts
• Demonstrated ability to work across the computational-experimental boundary (e.g., designed an analysis that informed a wet-lab decision, or interpreted assay data to guide a model)
• Familiarity with active learning or Bayesian optimization frameworks
• Experience building or working with agentic systems, LLM tool-use pipelines, or multi-step automated workflows
• Familiarity with prompt engineering and structured output parsing from language models
• Experience with workflow orchestration or pipeline tools (Databricks, Airflow, or similar)
• Comfort designing and consuming APIs or integrating across multiple tools/platforms programmatically
• Experience with software engineering best practices beyond scripting (testing, error handling, logging, modular code design)
• Familiarity with database interactions (SQL, querying structured data stores) in a production or semi-production context

Optional: Along with your application, please share a paper/preprint/software repo that best highlights your strengths so we can better understand the work you've led. If there is nothing public, please summarize that work in a few paragraphs. 

The pay range for this role is $1,400 to $1,500 per week, depending on experience. The duration of the internship is up to 10 weeks.

Octant is located in Emeryville, California and we work onsite.

Octant is an equal opportunity company that values applicants of all backgrounds. We’re committed to fostering an inclusive and supportive work environment. We value less traditional backgrounds, and may consider an equivalent combination of knowledge, skills, education, and experience to meet minimum qualifications. We know that confidence-gap and imposter syndrome can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you.

Quantum computing holds the promise of humanity’s mastery over the natural world, but only if we can build a real quantum computer. PsiQuantum is on a mission to build the first real, useful quantum computers, capable of delivering the world-changing applications that the technology has long promised.  We know that means we will need to build a system with roughly 1 million qubits that supports fault tolerant error correction within a scalable architecture, and a data center footprint.

By harnessing the laws of quantum physics, quantum computers can provide exponential performance increases over today’s most powerful supercomputers, offering the potential for extraordinary advances across a broad range of industries including climate, energy, healthcare, pharmaceuticals, finance, agriculture, transportation, materials design, and many more.

PsiQuantum has determined the fastest path to delivering a useful quantum computer, years earlier than the rest of the industry. Our architecture is based on silicon photonics which gives us the ability to produce our components at Tier-1 semiconductor fabs such as GlobalFoundries where we leverage high-volume semiconductor manufacturing processes, the same processes that are already producing billions of chips for telecom and consumer electronics applications. We also benefit from the quantum mechanics reality that photons don’t feel heat or electromagnetic interference, allowing us to take advantage of existing cryogenic cooling systems and industry standard fiber connectivity.

In 2024, PsiQuantum announced two government-funded projects to support the build-out of our first Quantum Data Centers and utility-scale quantum computers in Brisbane, Australia and Chicago, Illinois. Both projects are backed by nations that understand quantum computing’s potential impact and the need to scale this technology to unlock that potential. And we won’t just be building the hardware, but also the fault tolerant quantum applications that will provide industry-transforming results.

Quantum computing is not just an evolution of the decades-old advancement in compute power. It provides the key to mastering our future, not merely discovering it. The potential is enormous, and we have the plan to make it real. Come join us.

There’s much more work to be done and we are looking for exceptional talent to join us on this extraordinary journey!

Job Summary:

Are you eager to revolutionize life sciences using the transformative power of quantum computing? As a Quantum Life Sciences Chemist, you will lead efforts at the intersection of quantum computing, computational chemistry, and biology, solving critical challenges in drug design, biomolecular modeling, and biological systems simulation. By integrating quantum algorithms with established life sciences methodologies, you will pioneer new approaches to address complex problems in pharmaceuticals, biomaterials, and bioinformatics. Join our interdisciplinary team to advance quantum-enabled innovations and shape the future of life sciences.

At PsiQuantum’s Quantum Solutions team, your role will focus on bridging the gap between fault-tolerant quantum computing (FTQC) and established computational chemistry and life sciences tools. You will integrate these approaches with machine learning to explore novel workflows for quantum-informed drug discovery and biomolecular modeling. Your expertise in theoretical and computational chemistry will enable you to connect quantum-computed molecular insights with complex biological systems, driving advancements in drug design, biomaterials, and other critical areas within the life sciences.

This position requires a PhD in computational chemistry, biophysics, or a closely related field, preferably with postdoctoral research experience (although postdoc experience is not mandatory). We are looking for a curious, creative, and interdisciplinary thinker with a strong foundation in computational methodologies applicable to life sciences. The ideal candidate should be an avid reader of scientific literature, possess expert-level hands-on coding experience (e.g., Python, Fortran, C++), and have demonstrated skills in developing and applying computational techniques. Experience contributing to scientific software or modeling workflows is a plus. While prior knowledge of quantum information and fault-tolerant quantum computing is highly preferred, it is not required.

Responsibilities:

• Conduct innovative research, literature analysis, problem solving, and quantum workflow design in the areas of quantum-informed biomolecular modeling, drug discovery, and computational chemistry.
• Collaborate with quantum algorithm experts to identify areas where quantum computing can have the greatest impact in computational chemistry, biology, and life sciences.
• Contribute expertise in conventional (non-quantum-computing) algorithms to the development of in-house quantum algorithms. Serve as a technical lead in customer projects by collaborating with customers’ teams to integrate quantum computing-produced computational outputs into conventional life sciences workflows.
• Serve as a liaison between partner teams and PsiQuantum’s quantum information experts for innovative algorithm selection, development, and prioritization relevant to life sciences.
• Develop computational workflows that combine best-in-class conventional approaches (e.g., through high-performance computing (HPC)) with the breakthrough computational abilities of FTQC to reshape how quantum workflows are designed for life sciences applications.
• Serve as a subject matter expert in computational quantum chemistry and biomolecular modeling for PsiQuantum’s Quantum Solutions team, staying updated on recent academic literature, trends, and tools in life sciences.
• Foster collaboration across teams to maximize the impact of quantum algorithms and quantum computing-generated data in life sciences applications.
• Help shape external-facing materials that champion the applications of FTQC in the pharmaceutical, biotechnology, and life sciences industries (for key opinion leaders, media, and partners).
• Build and maintain external partnerships and collaborations on the topic, which can include meetings, group problem-solving sessions, or drafting research proposals, among others.
• Create organized internal reports and thoroughly document progress on assigned tasks.

Experience/Qualifications:

Required:

• Ph.D. in computational chemistry, biophysics, bioinformatics, or a closely related field, with a strong focus on computational methodology development, and 0 to 6 years of post-PhD (postdoctoral or industrial) experience.
• Hands-on experience with modeling and simulation of biological systems, such as protein-ligand interactions, enzymatic reactions, or biomolecular dynamics.
• Enthusiasm for working in a collaborative, interdisciplinary, and dynamic team environment.
• Expert-level Python coding skills with experience in scientific libraries relevant to life sciences.
• Proven ability to stay updated on recent academic literature and trends in computational chemistry and biomolecular modeling.

Preferred:

• Strong foundational knowledge of quantum chemistry methods (e.g., DFT, coupled cluster theory, or wavefunction-based approaches) and molecular simulation techniques as applied to biomolecular systems.
• Experience with free energy perturbation (FEP), molecular docking, or similar computational techniques for drug discovery.
• Experience with machine learning (ML) techniques in computational drug discovery, biomolecular modeling, or structural biology.
• Experience with coding GPU-accelerated molecular simulations.
• Familiarity with hybrid quantum-classical methodologies, such as QM/MM, applied to biomolecular systems.
• Knowledge of quantum embedding theories (e.g., DMET, embedded correlated wavefunctions) and their application to large, complex biomolecular systems.
• Hands-on experience with quantum computing or quantum algorithms, especially as applied to biological or chemical systems.
• General understanding of light-matter interactions or electronic excitations relevant to biological or chemical systems, such as energy transfer or photochemical processes.
• Familiarity with advanced quantum mechanical methods (e.g., CASCI, CASSCF) and their relevance to modeling enzymatic reactions or metal-containing biomolecules.
• Demonstrated scientific communication skills through peer-reviewed publications, conference presentations, or collaboration with industry partners.
• Expert-level C++ or Fortran coding skills.

PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, or any other basis protected by applicable laws.

Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to recruiting@psiquantum.com.

We are not accepting unsolicited resumes from employment agencies.

About the Role

We are seeking an exceptional Staff Computational Biologist to drive the next generation of software and data products supporting Target Identification and Prioritization across our research organization. This hybrid role is ideal for someone who thrives at the intersection of biology, computation, product strategy, and engineering execution.

As a senior member of the Translational Platform Engineering team, you will act as a product owner, technical strategist, and rapid prototyper, responsible for shaping the roadmap and delivering tools that power discovery teams. Your day to day includes working with biology data scientists to harden their notebooks and workflows, pushing new releases to production (on a predictable schedule), and sitting with biologists and chemists as they use the UIs to advance our translational biology efforts. The Staff Computational Biologist is the key to translating use cases into technical specifications for engineering teams.

This is a highly visible and impactful role where you will contribute to a human-biology-first approach to drug discovery programs by leading the end-to-end lifecycle of platform capabilities used daily by our Target ID scientists.

What You’ll Do…

• Own the product roadmap for Target ID software.
• Gather and prioritize scientific requirements from internal users.
• Translate use cases into technical specifications for engineering teams.
• Rapidly prototype computational solutions using Python.
• Develop and maintain internal packages, reproducible workflows, and APIs.
• Establish documentation, onboarding materials, and best practices for internal platform usage.
• Lead cross-functional project execution (data engineering, software engineering).
• Follow good engineering practices (i.e. CI/CD, predictable demo cadence, etc.)

What You Bring...

• Bachelor's/ Master's degree in relevant field (computational biology, bioinformatics, systems biology, computer science) or equivalent relevant education and experience
• 6+ years industry experience in computational biology or data-driven discovery; minimum 1 years’ experience in software engineering and data engineering teams
• Proficiency working with programming languages Python, and R, modern development frameworks and developing internal packages
• Experience with omics/translational data analysis, scalable ETL pipelines, data modeling, and associated QC
• 1+ years’ experience leading complex projects as product owner
• Experience supporting target identification, prioritization, or multi-modal analysis.

Nice to have...

• Experience with dashboard development (e.g. Shiny, Dash, Streamlit, React, Veu.js).
• Understanding of cloud-native tools and modern data platforms (AWS/GCP/Azure).
• Familiarity with the drug discovery and development process is a plus

About the Role:

Stylus Medicine is seeking an innovative, intellectually curious and team-oriented Principal Scientist to support our large serine recombinase (LSR) engineering platform. This individual will provide high-resolution efficacy and specificity analysis to advance our pipeline as well as support onboarding of new preclinical assays for regulatory submissions, ensure accuracy of our analysis pipelines and translate our wet lab experiments into computational insights that will enable engineering of our next generation LSRs.

Key Responsibilities & Accountabilities:

• Lead the analysis of NGS data from LSR experiments (like amplicon, hybrid capture, and long-read sequencing) to quantify target efficiency and specificity
• Build integrated workflows to annotate and characterize target sites by synthesizing proprietary datasets with large-scale public genomic databases
• Design, implement, and scale robust computational pipelines for multi-omics analysis
• Collaborate closely with the Screening, Genome Engineering, and Protein Engineering teams to design experiments and interpret results
• Develop and maintain internal databases and infrastructure to ensure experimental results are accessible, reproducible, and actionable
• Contribute to patent filings, regulatory submissions, and scientific publications

Qualifications & Skills:

• PhD with 5+ years or Master’s with 10+ years (or Bachelor’s with 12+ years) of industry experience in Computational Biology, Bioinformatics, or a related quantitative discipline.
• Strong expertise in experimental design, data processing, statistical analysis, and NGS data analysis
• Expert-level proficiency in Python and/or R, with extensive experience using data science libraries (e.g., Pandas, NumPy, Bioconductor)
• Experience with cloud computing platforms for large-scale data processing and with workflow management systems
• Excellent organizational, communication, and documentation skills, with demonstrated ability to work effectively in collaborative, interdisciplinary environments
• Strong scientific critical thinking skills, including the ability to evaluate approaches, synthesize complex data, and provide actionable recommendations
• Proven track record of working successfully across cross-functional teams with proactive communication and timely delivery

Pay Range: $180,000 - $195,000

Position Summary: 

 We are seeking a highly skilled and motivated Contract Scientist – Translational Biology to support mechanistic hypothesis testing and sample generation for rilparencel, our autologous kidney cell therapy currently being evaluated in a Phase 3 clinical study, as well as next-generation cell therapy programs. This role will focus on primary human tissue/cell culture models (BSL-2) and the execution of multi-condition studies that generate high-quality samples for downstream molecular and NGS-based readouts. In partnership with the Translational Biology team, this scientist will contribute to experimental design and method development for workflows involving small human biopsy-derived samples, with an emphasis on reproducible execution, rigorous sample tracking, and clear communication of results.  

Essential Duties & Responsibilities: 

Primary Human Tissue Culture (BSL-2) & Model Execution 

• Establish, maintain, and troubleshoot primary human kidney tissue/cell cultures using strict aseptic technique and contamination prevention. 

Experimental Design & Method Development  

• Develop and execute experimental plans with the translational team to test mechanistic hypotheses in vitro (e.g., media perturbations, multi-factor time courses), including appropriate controls and replicates. 

• Contribute to method development/optimization for primary tissue workflows (e.g., tissue handling, digestion/single-cell prep where applicable, culture conditions, sampling strategy, preservation), documenting protocol iterations and outcomes. 

• Execute complex study layouts with many conditions, timepoints, replicates, etc when required. 

Sample Processing & Molecular Assays 

• Harvest tissue/cells and perform RNA/DNA/protein/metabolite extraction, quantification, and basic QC (e.g., yield, purity; integrity checks where applicable). 

• Run and troubleshoot core molecular assays, such as RT-qPCR, ELISA, Western blot, and/or reporter assays (e.g., luciferase), including control selection. 

• Prepare assay- and omics-ready sample sets with complete metadata for internal use and/or external partners, as needed. 

NGS Library Preparation & Omics Support 

• Perform NGS library preparation for approaches such as RNA-seq, ATAC-seq, and CITE-seq (bulk and/or 10x single-cell), including essential QC steps (quantification, sizing where applicable, yield assessment). 

• Support handoff of libraries/samples to sequencing vendor pipelines, maintaining traceability of sample IDs, library indices, and processing conditions. 

Documentation & Communication 

• Maintain high-quality experiment documentation (ELN) and accurate sample inventories (LIMS). 

• Participate in interpretation translational data to uncover key insights for cell therapy mechanism of action elucidation. 

• Communicate findings effectively across cross-functional teams, including research, process & analytical development, and clinical translation groups. 

• Contribute to regulatory filings, scientific publications, and presentations at key industry and academic conferences. 

 Qualifications: 

Education/Training 

• M.S. or Ph.D. in Cell Biology, Molecular Biology, Immunology, Bioengineering, or related field.  

Required Experience & Skills 

• Demonstrated hands-on experience with primary human tissue/cell culture and comfort working with human-derived materials in a BSL-2 environment. 

• Experience executing multi-condition in vitro experiments with strong attention to detail and sample tracking. 

• Experience with RNA/DNA/protein extraction and basic QC/quantification. 

• Experience with at least two of: qPCR/RT-qPCR, ELISA, Western blot, reporter assays. 

• Hands-on experience with NGS library preparation for one or more of: RNA-seq, ATAC-seq, CITE-seq (bulk and/or single-cell). 

• Able to work effectively in a fast-moving R&D environment with multiple parallel experiments and time-sensitive sample processing needs. 

Preferred 

• Flow cytometry and/or FACS experience (sample prep, staining, acquisition and/or sorting workflows). 

• Familiarity with common bioinformatics/QC concepts and tools used in sequencing workflows; familiarity with at least one scripting language (Python and/or R). 

Skills:  

• Ability to work in a fast-paced environment and collaborate across disciplines 

• Strong team player 

• Goal-oriented mindset 

• Ability to focus efforts & complete deliverables on-time 

• Certifications/Licenses: Licenses / Certification welcome 

At Atomic AI, we build artificial intelligence to pioneer new frontiers in drug discovery. Our unique R&D platform, an early version of which was featured on the cover of Science, provides new strategies to treat previously undruggable diseases by targeting RNA. We continue to advance this platform by developing new machine learning methods and unique foundation models fueled by our large-scale, in-house experimental data collection. We are an interdisciplinary team of scientists and engineers and believe our people are our greatest strength and the key to our success.

The opportunity

As a full-time Data Scientist on the Machine Learning team, you will work closely with scientists and engineers to apply and advance our technology platform for RNA structure prediction, target identification, and early-stage drug discovery. You will lead the curation of RNA-focused datasets for ML training and validation, discover statistical patterns in our large-scale datasets evaluating RNA structure and RNA-small molecule interactions, and devise and implement new strategies to test the accuracy of our ML models. Your analysis will guide the development of improved ML models and the targeted acquisition of new experimental data.

This is a hybrid position with three days in-person at our South San Francisco office.

Responsibilities:

• Provide RNA biology and RNA structure expertise on the ML team.
• Enable and apply our RNA-structure platform to prioritize RNA targets for small-molecule therapies and advance structure-based drug discovery.
• Generate insights from datasets on RNA structures and small molecule interactions (e.g. chemical probing, RNA-SM screens) by conducting statistical analyses, interpreting biological noise, and applying RNA domain expertise.
• Curate RNA datasets for training of ML models, help evaluate model performance, and provide directions for improvement.
• Inform scientific questions and ML model development in early-stage RNA drug discovery.
• Collaborate with the internal wetlab team and shape the design of experimental assays on RNA structure and RNA-SM interactions.
  
  

About you:

• Ph.D. in Computational Biology, Bioinformatics, Statistics, Biophysics, or related field, or equivalent experience.
• Expertise in RNA biology and biochemistry, RNA-protein interactions, and RNA structure.
• Proficiency in Python for data curation and analysis at scale, and fluency with libraries for data analysis (NumPy, pandas) and applied ML (scikit-learn).
• Strong programming background, familiarity with Unix and comfort with using external software packages.
• Strong foundation in statistics and experience with conducting statistical analysis of large-scale datasets.
• Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.
  
  

Pluses:

• History of scientific achievement, e.g. as evidenced by publication of impactful papers.
• Conceptual understanding of ML model development and evaluation, and experience using ML models.
• Experience with computational structural biology tools for modeling RNA secondary and tertiary structure (e.g. Rosetta, AlphaFold, RNAfold).
• Understanding of RNA-SM interactions, including familiarity with structural properties of binding sites and experimental methods for evaluating binding.
• Proficiency with pipelines for next-generation sequencing dataset processing.
• Exposure to high throughput experimental assays for evaluating RNA structure and screening RNA-SM interactions.
  
  

Salary Range: $135,000/year to $180,000/year + equity + benefits. This range reflects variations in seniority, expertise, and skills. 

General Application: Join Absci and Redefine Possible

Job Description

At Absci, we are always on the lookout for extraordinary talent to help us redefine the boundaries of science and innovation. While we may not have your dream job listed today, we encourage you to submit a general application. By doing so, you’ll be the first to know when the right opportunity becomes available tomorrow.

Areas of Focus

• Drug Discovery (In-Vitro and In-Vivo bioassays)
• Translational Research
• Protein Engineering and Structural Biology
• Analytical Chemistry
• Protein Purification
• Fermentation
• Bioinformatics
• Software Engineering and Data Science
• Machine Learning and AI
• Business Development
• Corporate (Legal, Administration, Finance, HR, etc.)

Qualifications

We are seeking candidates who embody Absci's core values and are eager to immerse themselves in our innovative and collaborative company culture.

Successful candidates will thrive in our dynamic innovative environment and contribute as key members of project teams. If you share our vision and are excited to be part of a team that’s redefining possible, we invite you to join us.

Submit your application today and become an Unlimiter at Absci!