The Team

The Biohub in New York is an independent nonprofit research institute that brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Biohub itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies. We are guided by our values of scholarly excellence; disruptive innovation; hands-on engineering/hacking/building; partnership and collaboration; open communication and respect; inclusiveness; and opportunity for all.

Our Vision                                                                     

• We pursue large scientific challenges that cannot be pursued in conventional environments
• We enable individual investigators to pursue their riskiest and most innovative ideas
• The technologies developed at Biohub facilitate research by scientists and clinicians at our home institutions and beyond

Diversity of thought, ideas, and perspectives are at the heart of Biohub and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution.

The Opportunity

The van der Stegen Lab at Biohub NY studies human immune cell development from induced pluripotent stem cells and designs engineering strategies to harness immune cells for therapeutic applications. We are looking for a Computational Biologist to join our team to further expand our evaluation of immune cell lineage commitment, function and how genetic engineering strategies can affect those. 

The Computational Biologist will possess deep expertise in the analysis of single cell transcriptional data, including developmental trajectory analysis, and ideally also have experience with proteomics datasets. They have an interest in hematopoiesis and immune cell biology and can demonstrate the intention to apply state-of-the-art analysis tools through close collaboration with the data science team at Biohub.

What You'll Do

• Implement and create analytical pipelines for transcriptomics, including chemical and/or genetic perturbations, and multi-omic datasets
• Support immunologists in experimental design for transcriptomic and multi-omic analysis
• Support immunologist in the experimental design of CRISPR screens
• Analyze scRNAseq, CITE-seq, scATACseq, TCR/BCRseq and Mass Spectrometry datasets
• Incorporate publicly available datasets with in-house generated datasets
• Support new hypothesis generation 
• Present research findings in academic journals and conferences

What You'll Bring

• PhD degree in computational biology, systems biology, immunology, bioengineering or a related field.
• Experience working with hematopoiesis-, immunology- or developmental biology-related datasets
• Experience analyzing data from perturbational screens (e.g. perturb-seq)
• At least 4 years of programming experience in R and/or Python
• Ability to communicate effectively with wet-lab biologists
• Expertise in bioinformatics including computational pipelines for analyzing bulk and single-cell genomics (Scanpy, Seurat, etc)
• Ability to work efficiently in HPC or cloud compute (e.g. AWS) environments
• Strong written and verbal communication skills
• Experience in presenting research findings
• Track record of publishing in peer-reviewed journals 
• 3+ years of experience with large scale immune data (single cell sequencing, T and B cell receptor profiling, mass spectrometry)
• Demonstrated ability to deliver multiple large biological data products, deploying QC best practices
• Experience with proteomic analysis datasets including flow cytometry and mass spectrometry
• Experience with spatial transcriptomics
• Familiar with metabolomic datasets
• Committed to writing well-commented code and documentation, and familiarity with coding best practices (i.e. version control, code review)

Compensation

The New York City, NY base pay range for a new hire in this role is $153,000 - $210,100. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

This position may be eligible to participate in Biohub's discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with Biohub's total rewards philosophy and may vary by role.

Better Together

As we grow, we’re excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team’s manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.

#LI-Onsite

The Impact You’ll Make

As a key member of Recursion's partnership-facing data science team, you will be at the forefront of reimagining drug discovery from first principles using Recursion’s massive data and compute capabilities. As senior computational biologist, you will be supporting a portfolio of partnership preclinical drug programs and be responsible for designing and executing analyses to support target nomination, validation, and early programs in neuroscience diseases.

You will integrate layers of Recursion platform data (phenomics, transcriptomics, proteomics, etc) to validate the link between target and disease biology and to propose targets and early programs in novel areas of neuroscience. You will partner with biologists and medicinal chemists to build supporting data packets for targets from our phenomic maps, target screens, and partnered patient data sets. You will also collaborate with computational scientists from across the organization to develop, deploy, and scale novel approaches to: 1) translational validation in hit to lead, 2) mechanism-of-action identification/de-risking, and 3) build evidence for patient connectivity to match the targets we are validating and medicines we are creating to the patients who need them.  

In this role, you will:

• Deliver biological insights on therapeutic candidates and disease biology from the analysis of high-dimensional (phenomics, transcriptomics, proteomics, patient-derived) datasets that support clinical development planning
• Evaluate the biological and molecular evidence for therapeutic hypotheses and accelerate drug program progression into the clinic
• Synthesize diverse datasets (internal and external) to generate and evaluate hypotheses for drug discovery, biomarker development, mechanism of action and target population identification
• Present data analysis to decision makers and stakeholders in a clear and compelling way that drives toward getting medicines to patients
• Assess new data sources, develop and scale new analysis methods, and support key program decisions with the ultimate goal of bringing life-changing therapies to patients at unprecedented speed
• Industrialize analysis approaches to not only solve for the current project, but also to accelerate future projects and scale the impact that we can have
• Collaborate cross-functionally with Recursion’s data science, biology, medicinal chemistry, and  platform, teams to further advance Recursion’s ability to interpret and translate large-scale data assets into therapeutic programs

The Team You’ll Join 

Our group is a bold, agile, diverse collective of computational drug discovery scientists and data scientists deeply focused on the singular goal of bringing new therapeutics into the clinic at an accelerated pace. We are a computational group that spans precision oncology, neuroscience, and I&I (immunology and inflammation), and focuses on advancing novel, targeted therapies for these disease areas. We partner closely with our biologists and medicinal chemists to design and execute impactful and decisional data analysis for multiple programs. We are responsible for data strategy across the portfolio and supported by computational leadership in designing scalable and reproducible experiments that serve to advance multiple programs within the portfolio. 

Our team collaborates extensively with computational biologists in other therapeutic areas (immunology, oncology, etc.) as well as data scientists and engineers from our core platform teams to provide a strong network of feedback and support. 

The Experience You’ll Need

• PhD in a relevant field (computational biology, systems biology, bioinformatics, neuroscience, etc.) with a very strong computational focus and 5+ years of experience in biotech or pharma industry OR MS in a relevant field
• Experience applying computational methods (including probabilistic, statistical, and/or machine learning techniques) to analyze and integrate matched human clinical and molecular data in a high-level programming language such as Python or R
• Deep expertise in the analysis and data integration of one or more ‘omics data modalities (phenomics, transcriptomics, proteomics, genomics) and/or human clinical data
• Exceptional data visualization skills
• Excellent cross-functional communication skills, including an ability to explain complex scientific concepts to a variety of audiences using a combination of plots, documents, and presentations

Nice To Have:

• Strong understanding of patient genetics and historical druggability of disease-relevant pathways,  including experience working with patient data
• Experience in efficiently advancing drug programs from proof of concept and into clinical development
• Experience with neuroscience clinical trial biomarker analysis
• Experience working as part of partnerships or client facing (consulting) teams

Working Location & Compensation:

This is an office-based, hybrid role in either our Salt Lake City or New York City offices. Employees are expected to work in the office at least 50% of the time.

At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $200,600 to $253,100. You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. 

#LI-EP1

The Impact You’ll Make

As a computational biology specialist on our Target ID team, you will be at the forefront of transitioning Recursion to its next era of drug discovery. You will serve as a critical biological anchor for a highly technical data science team building the next generation of our target discovery pipelines.

The team’s mission is to identify novel therapeutic targets at scale across the genome for hundreds of indications. You will have access to all of Recursion's data layers—including massive internal maps, functional genomics, and rich patient data (transcriptomics, genetics, and Real-World Data/EHR)—and will be tasked with proposing, piloting, and deploying new methods to integrate these datasets.

Crucially, you will leverage your biological subject matter expertise to orient and focus your data scientist and software engineer peers towards reliable and correct usage of biological data and feasible candidate programs. As we build out semi-automated and agentic tools (e.g., multi-agent LLM systems for portfolio oversight and target assessment), your deep real-world biology experience will guide the development of these tools, ensuring they are grounded in biological reality and translate to meaningful portfolio and patient impact.

The ideal candidate is a computational biology specialist with high fluency in data science tech stacks. You know how to build and evaluate predictive models and build agentic pipelines, and your differentiator is your deep understanding of patient-relevant datasets, disease biology, and target discovery.

In this role, you will:

• Discover & Evaluate: Propose and validate novel targets using deep integration of patient data (transcriptomics, population genetics, EHR, etc) and Recursion's internal multi-omic data layers.
• Guide & Automate: Collaborate closely with data scientists to build, refine, and guide semi-automated and agentic target discovery tools. You will ensure these tools are biologically sound and can scale to evaluate hypotheses across many indications spanning a wide range of therapeutic areas.
• Triangulate: Use advanced statistical methods (e.g., causal inference, survival modeling) to establish confident target-to-patient connections and define specific addressable patient populations for early pipeline programs.
• Bridge the Gap: Translate complex platform findings into disease-relevant applications, bridging the gap between high-dimensional data science output and actionable drug discovery insights.
• Present & Influence: Communicate complex biological rationale and data analyses to decision-makers and cross-functional stakeholders, driving data-backed "go/no-go" decisions in a two-stage target approval process.

The Team You’ll Join

Our group is a bold, agile, diverse collective of data scientists and computational biologists driving Recursion’s early portfolio strategy. We are focused on aggressively expanding our early-stage pipeline with highly validated, novel therapeutic targets. To achieve this, we prioritize defining specific patient populations and establishing clear, data-backed translational paths from day one of every new program.

Because this team is dominated by experts in traditional data science, AI/ML, and software engineering, your role is absolutely critical. You will provide the essential biological experience and subject matter expertise to improve and accelerate the work of your peers. Essential attributes for this role include a bold, execution-first attitude, high technical fluency to collaborate seamlessly on data-science-heavy codebases, and a passion for deploying rigorous science to develop life-changing medicines.

The Experience You’ll Need

• PhD in Computational Biology, Bioinformatics, Human Genetics, Systems Biology, or a closely related field with 3+ years of experience in the biotech or pharma industry OR MS in a relevant field and 5+ years of industry experience focusing on target ID or early drug discovery.
• Biological SME: Deep, real-world experience in target discovery, functional genomics, and understanding the druggability of disease-relevant pathways.
• Data Science Fluency: Highly proficient in Python and/or R, with a strong ability to seamlessly integrate into a data-science-heavy tech stack. Comfortable with modern software engineering practices, cloud computing, and machine learning concepts.
• Patient Data Expertise: Extensive experience working with "discovery-related" human data, particularly transcriptomics (bulk/single-cell), patient genetics/GWAS, and clinical/real-world data (e.g., EHR).
• Analytical Rigor: Experience applying advanced computational and statistical methods to establish biological causality (e.g., survival analysis, causal inference modeling).
• Excellent cross-functional communication skills, with a proven track record of upskilling peers in biological concepts and guiding technical teams toward translatable biological outcomes.

Nice To Have:

• Experience working with, prompting, or integrating Large Language Models (LLMs) and autonomous agentic workflows into scientific research.
• Familiarity with building or utilizing Knowledge Graphs for target identification.
• Experience working in the field of oncology or immunology.

Working Location & Compensation:

This is an office-based, hybrid position at our US headquarters located in Salt Lake City, Utah. Employees are expected to work in the office at least 50% of the time.

At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $151,800 to $230,000. You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. 

#LI-EP1

Position Summary

We are seeking a Computational Biologist who is passionate about using data-driven, scalable methods to reveal biological insights. The ideal candidate is an independent thinker with strong computational and quantitative skills, and the ability to collaborate closely with both experimental and computational scientists. You will design, implement, and scale computational pipelines for single-cell perturbation datasets, while contributing to model development and experimental design.

This is a unique opportunity to join a dynamic, interdisciplinary environment and help shape Neptune Bio’s computational strategy and infrastructure.

Key Responsibilities

• Develop, innovate, and maintain advanced computational methods to process, analyze, and interpret large-scale single-cell genomics and perturbation datasets.
• Collaborate with wet-lab and computational teams to integrate data from diverse experimental modalities and guide experimental design.
• Build, optimize, and scale data analysis pipelines using modern cloud computing environments (e.g., AWS, GCP, Azure).
• Contribute to Neptune Bio’s data infrastructure, ensuring reproducibility, scalability, and efficient access to large datasets.
• Stay current with advances in computational biology, machine learning, and scalable infrastructure, applying them to ongoing research challenges.
• Communicate findings clearly through reports, visualizations, and presentations to multidisciplinary audiences.

Qualification and Education Requirements

You must have:

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field, OR equivalent experience (e.g., BS/MS with ≥3 years of relevant experience).
• Proficiency in Python, R, and Unix/Linux environments
• Demonstrated experience in single-cell or multi-omics data analysis.
• Solid understanding of statistics, data modeling, and modern machine learning approaches.
• Experience deploying and scaling computational pipelines on cloud platforms (AWS, GCP, or similar).
• Strong communication skills and enthusiasm for working in a collaborative, fast-paced environment.

Additional preferred experience includes:

• Background in functional genomics, CRISPR screens, or perturb-seq analysis.
• Experience integrating multi-source data to derive novel and impactful insights.
• Expertise in data engineering and reproducible research tools (e.g., Docker, Nextflow, Snakemake) as well as familiarity with cloud-native architectures and distributed compute.
• Strong publication record demonstrating innovation in computational methods or biological data analysis.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.