About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

About the Position

We are searching for an exceptional scientific leader to establish a new team within Arc Institute’s Computational Technology Center, serving as the Director, Machine Learning for our Alzheimer's Disease Initiative (ADI). 

This ambitious initiative spans Arc's Technology Centers and Core Investigator Laboratories and focuses on high-throughput interrogation of neurodegeneration and Alzheimer's disease mechanisms using advanced gene editing and functional genomics approaches. As the Machine Learning Research Lead, ADI, you will spearhead development of sophisticated machine learning foundation models to capture cell states and infer gene regulatory networks and causal relationships to predict therapeutic interventions.

This position offers the rare opportunity to build and lead a world-class team while making direct contributions to understanding and potentially treating Alzheimer's disease through state-of-the-art computational biology and machine learning approaches.

About You

• You are passionate about machine learning and computational biology, with expertise in applying cutting edge ML approaches to biological systems
• You excel at developing interpretable machine learning approaches, such as variational inference and causal modeling methods
• You are excited about building and leading a technical team while remaining hands-on with foundation model development and implementation. 
• You thrive in collaborative, multidisciplinary environments and enjoy working with both computational scientists and wet lab biologists
• You are a continuous learner who stays current with the latest developments, in both machine learning and neuroscience

In This Position, You Will

• Attract, build and lead a team of exceptional machine learning research scientists dedicated to developing foundation models for cellular systems in Alzheimer's disease
• Develop and execute on a roadmap of interpretable machine learning approaches to understand disease mechanisms, with emphasis on variational inference, causal modeling, as well as modern transformer- and diffusion-based architectures
• Work closely with experimentalists on brain organoid/spheroid cellular models as well as in vivo models, working with scRNA-seq, Perturb-seq and other datasets to unravel causal gene pathways relevant to Alzheimer’s disease
• Develop predictive modeling approaches to identify how perturbations can move cell states from high risk Alzheimer’s profiles back to healthy / low risk states
• Collaborate closely with experimental biologists to ensure ML models are grounded in disease biology and can feedback into future experimental strategies
• Foster collaborations with external partners in the computational biology and neuroscience communities
• Publish high-impact research through preprints, journal publications, open source code, and presentations at leading conferences

Required Qualifications

• PhD in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or related quantitative field
• 7+ years of relevant experience with a minimum of 3 years of people management experience
• Strong research background with experience in academic settings (university, research institute) and/or biotech/pharmaceutical industry with a focus on scientific innovation
• Proven expertise in machine learning applications to biological datasets, with specific experience in single-cell profiling data and foundation model development
• Deep experience with interpretable machine learning approaches for biological systems (e.g. variational inference methods).
• Advanced technical skills in machine learning frameworks, particularly PyTorch, and ideally experience with model training at scale
• Publications in top-tier journals in computational biology and machine learning
• Excellent communication skills with ability to present complex machine learning concepts to both computational and biological audiences
• Proven ability to remain technically hands-on while providing effective team leadership, mentorship, and management
• Background in neurodegeneration research including familiarity with Alzheimer's disease datasets, pathways, networks, disease mechanisms, and eQTL analysis is a plus 

The base salary range for this position is $380,000-$420,000. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

Why this position could be the best job you’ve ever had?

• Work at the center of AIxBio with the potential to revolutionize drug discovery for the world.
• Work in a unique environment that incorporates both wet lab data generation and frontier AI modelling in an active learning loop.
• Join a new type of research org that fuses high-velocity execution of a startup with the intellectual rigor of a world-class academic institute, with a long runway to tackle some of the hardest - and highest potential -  challenges in science today.
• Collaborate with some of the most accomplished scientists and entrepreneurs in the world.

About the position

We are searching for an innovative scientific leader experienced in building predictive models based on single-cell genomic data. The chosen candidate will spearhead the development and application of advanced machine learning models tailored for perturbative gene expression modeling, in the context of Arc’s virtual cell initiative.

About you

• You are passionate about machine learning, ideally with experience or strong interest in biology and single-cell genomics.
• You want to develop highly innovative and accurate biology-inspired multimodal machine learning models.
• You are excited about collaborating with a multidisciplinary team of computational and experimental biologists at Arc.
• You are a strong communicator, capable of translating complex technical concepts at the intersection of machine learning and biology.
• You are a continuous learner.
• You are interested in recruiting and managing your own group of scientists and engineers as well as mentoring and training for other scientists.

In this position you will

• Lead/build a team of 6 ML research scientists and engineers augmented with undergrad/masters/PhD students to contribute to the development of a state-of-the-art foundation model and agentic framework for understanding how cells respond to perturbations.
• Work in an active learning loop with Arc’s wet lab scientists to shape the world's largest and most diverse set of single cell training data across many cell contexts.
• Collaborate closely with other research groups to integrate genomics, functional track,and omics data more broadly beyond scRNA-seq data and Perturb-seq
• Stay up to date on the latest in frontier ML research and pioneer new architectures and approaches.
• The ultimate goal is to build a high utility virtual cell model for use by biologists worldwide. We publish our breakthroughs to widely accelerate scientific progress and partner with some of the biggest names in AI.
• Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others. 
• Attract the very best talent in the world to support VCI initiative goals

Requirements

• PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field.
• Minimum of 5 years of experience working in/with machine learning, well versed in frameworks such as Pytorch, TensorFlow, JAX, etc.
• Proven experience leading research teams in a fast paced, multi-disciplinary environment.
• Experience with or strong interest in biology with ability to communicate and collaborate successfully with biologists and pure ML engineers.
• Excellent communication skills, both written and verbal, with a strong track record of presentations and publications.

The base salary range for this position is $380,000-$420,000. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

Why this position could be the best job you’ve ever had

• Bridge the Gap Between Data and Discovery: Move beyond standard pipelines. You will lead our "Tertiary Analysis" work, transforming raw counts into mechanistic analyses that explain how genes, drugs, and environments collide.
• Join a New Type of Research Org: Work within a structure that fuses the high-velocity execution of a startup with the intellectual rigor of a world-class academic institute.
• Command "Gold Standard" Datasets: Gain exclusive access to massive, full-production datasets - from T-cells and NGN2 neurons to deep chemogenetic screens - designed specifically for large-scale discovery.
• Lead with Autonomy: While a sister team handles the essential bioinformatics infrastructure and QC, your mandate builds on top of this by developing the novel methods and analyses needed to uncover new biology (e.g. gene-module detection tools, etc).
• Advancing the field: We publish our breakthroughs to widely accelerate scientific progress and partner with some of the biggest names in AI

About you

• Biological Mechanism Minded: You aren't satisfied with a list of differentially expressed genes. You are obsessed with the "why": building explanatory models that map the complex interactions between genetics, compounds, and the cellular environment.
• Empathetic Leader: You enjoy and derive energy from the "human" side of science. You are a dedicated mentor who views the professional and scientific growth of your team as one of your primary metrics of success.
• Scientific Translator: You are a rare hybrid who speaks the language of both the wet lab and bioinformatics. You can debate mechanistic biology with a neuroscientist and then pivot to discuss algorithmic efficiency with a tool-builder.
• Production Scaled: You have experience working with massive, "full-production" datasets. You know how to extract biological signal from T-cell assays or chemogenetic screens at scale in a fast paced, collaborative environment.

In this position you will

• Build and manage Arc’s Computational Biology team.
• Actively mentor and provide guidance to research staff, developing them both professionally and scientifically.
• Develop and refine cutting-edge tertiary analysis and explanatory modeling approaches across Arc’s key research areas, including functional genomics, transcriptomics, epigenomics, and proteomics.
• Integrate multiple data types to elucidate functional connectivity between genes, transcripts, and proteins, with the goal of building mechanistic models of gene networks and interactions.
• Be a key participant in a collaborative, Institute-wide initiative on functional genomics focused on building virtual cells and the mechanistic understanding of late-onset Alzheimer’s disease.
• Partner with Arc’s Core Investigators and Technology Centers to advance research across the institute and create a culture of collaboration and excellence.
• Engage in and manage internal and external research collaborations.
• Attend and present at team meetings to share results, plan projects and experiments, and ensure that projects support team goals.

Job Requirements

• PhD, MD, or MD/PhD in a relevant field and 12+ years of relevant experience in industry and/or academic settings; including 5+ years of experience managing, leading, and growing scientific teams. 
• Extensive experience with genomics, transcriptomics, epigenomics, and single cell sequencing data analysis. 
• Experience developing innovative computational algorithms to address biological questions.
• Outstanding written and verbal communication skills are required for research presentations, SOP development, and publications. 
• The successful candidate will be an ambitious self-starter, be motivated to apply his/her skills to diverse projects, and enjoy working in a fast-paced team environment

The base salary range for this position is $233,500-$287,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

About the position

We are seeking a highly skilled and motivated Senior Research Associate to join the Molecular Engineering team within the Genome Engineering Technology Center at Arc for a fixed term of six months to support the execution of arrayed genetic perturbation screens in disease-relevant human pluripotent stem cell (hPSC)-derived cells. In this position, you will play a key role in our Molecular Engineering platform development efforts for end-to-end lentiviral gRNA delivery to differentiated cells by executing, evaluating, and optimizing protocols to efficiently deliver high levels of perturbations into cells that will be incorporated into 2D and 3D brain models by our collaborators in the Cellular Models Tech Center. Through this work, you will play a critical role in the Institute's Alzheimer's Disease Initiative, an ambitious cross-functional effort aimed at identifying and developing drugs for rational therapeutic targets to combat devastating neurodegenerative disorders.

The ideal candidate will have experience and proficient skills in stem cell culture and functional characterization of engineered cells, with expertise in implementing, running, and troubleshooting workflows with an outstanding attention to detail. This is an excellent opportunity for a highly motivated and curious researcher interested in helping translate genomic insights into therapeutic strategies by contributing to a pioneering platform that has the potential to transform our understanding and treatment of Alzheimer's disease and related disorders. 

About you 

• You love science and learning. Whether it’s gaining knowledge in new fields of scientific research or learning a new lab technique, you never stop being curious and routinely enjoy stepping out of your comfort zone to learn new things. 
• You are flexible and adaptable, eager to try new ways of tackling problems beyond the approaches with which you’re familiar while also bringing energy and curiosity to the optimization of existing approaches.
• You have a creative and curious spirit, open and eager to try new ways of tackling problems beyond the approaches with which you’re familiar.
• You can work fast and are detail-oriented. You are careful and diligent about good documentation practices and keeping things organized while moving at a rapid pace.
• You show initiative and can effectively work independently while also adapting well to situations where collaboration and communication with other RAs / Scientists will bring the best results.
• You are comfortable carrying out the routine execution of tasks while identifying opportunities to troubleshoot and improve bottlenecks.
• Your organizational skills enable you to manage multiple concurrent projects, and your curiosity and creativity drive you to continuous learning and innovation.

In this position you will

• Execute routine stem cell culture and differentiation protocols.
• Conduct and optimize lentiviral transduction-based experiments to introduce arrayed genetic perturbations into engineered cell lines.
• Leverage in vitro cell-based assays (flow cytometry, imaging, immunostaining, etc.) and molecular biology techniques to characterize the functional activity of genetic perturbed cells.
• Support the cross-functional execution of arrayed genetic perturbation screens for the Alzheimer’s Disease Initiative at Arc.
• Have a systematic approach to the execution of tasks and experiments with a focus on efficiency and reproducibility.
• Maintain careful records in ELN (electronic lab notebook) and organize materials and reagents with detailed tracking in our LIMS system.
• Troubleshoot and identify opportunities to improve existing protocols and platform capabilities. 
• Analyze and present data and at internal meetings and seminars.

Requirements

• BS/MS or equivalent professional experience in Biology, Biotechnology, Genetics, Cellular Biology, or relevant fields.
• With a BS degree, 4+ years of relevant experience or with a MS degree, 0-2+ years of relevant postgraduate experience. Industry experience is desirable but not required.
• Relevant lab experience including demonstrated and proficient skills for stem cell and progenitor cell culturing and routine characterization. 
• Familiarity with CRISPR-Cas9 or other genome editing or genetic perturbation techniques, with hands-on experience functionally characterizing genetically modified cells. 
• Experience running and analyzing flow cytometry experiments, including familiarity with running multi-color panels, immunostaining experiments, and FlowJo analyses. 
• Detail-oriented with excellent organizational and time management skills.
• Strong oral and written communication skills. 
• Ability to multitask, willingness to learn, and work in a highly collaborative environment.

Preferred Qualifications:

• Proficiency and experience with molecular cloning, virus production, and cell line engineering. 
• Experience with LIMS systems, ideally Benchling.
• Experience analyzing large data sets preferably using data scripting tools such as Python or R.

The base monthly rate range for this position is $7,290 - $9,520. These amounts reflect the range that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits.

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

About the position

We are seeking a highly skilled and motivated Senior Research Associate with a strong background in single-cell RNA-seq to join the Virtual Cell Initiative at Arc Institute. In this role, you will contribute to the generation of large-scale single-cell perturbation datasets across 50+ cancer cell lines to train Virtual Cell models to make accurate predictions of cellular state and their response to intervention.

You will use your experience implementing single-cell genomics technologies to scale our workflows for generating high-quality scRNA-seq datasets and contribute to critical data generation for Arc’s Virtual Cell Initiative. As part of a highly collaborative team, you will have opportunities to build expertise in cell line engineering, mammalian cell culture, and CRISPR screening. This role is ideal for someone who is detail-oriented and motivated by optimizing experimental workflows. The successful candidate will have excellent time management and communication skills and will thrive within our vibrant and collaborative culture.

About you

• You are passionate about working at the intersection of high-throughput biology and AI/ML to advance human health.
• You are process-oriented and are motivated by optimizing workflows for efficiency and scalability.
• You thrive in a timeline-driven, dynamic, team science environment.
• You hold yourself to a high standard of rigor and consistency in your experimental work.
• You are detail-oriented and maintain thorough documentation practices.

In this position you will

• Execute single cell genomics workflows, including sample processing, NGS library preparation, and QC.
• Support Arc’s Virtual Cell Initiative CRISPR screening efforts by working collaboratively to generate large in vitro gene perturbation datasets across many cell contexts.
• Optimize and troubleshoot our single cell sequencing and CRISPR screening workflows to maximize data quality, diversity, and scalability.
• Streamline high throughput experiments by implementing automation solutions.
• Utilize project management systems to track progress and ELN/LIMS  systems to document experimental data.
• Communicate experimental progress and results at group and cross-functional meetings.

Requirements

• BS + 4 years or MS + 2 years of professional experience in cellular biology, molecular biology, biochemistry, neuroscience, or another relevant field. 
• Expertise in running single cell RNA-seq workflows, including cell sample preparation, single cell capture, and library preparation. Experience with 10X Genomics technology is a plus.
• Hands-on experience with common molecular biology techniques, including PCR/qPCR/ddPCR, DNA and RNA purification, and nucleic acid QC and quantification (e.g., TapeStation, Qubit).
• Proficiency in aseptic technique for culturing mammalian cell lines.
• Strong attention to detail and ability to follow experimental protocols precisely.
• Experience using an ELN to document your work and track biological material. Familiarity with Benchling is a plus.
• Excellent written and verbal communication skills and a collaborative mindset.

Preferred Qualifications

• Experience working in an industry setting is desirable but not required.
• Experience implementing liquid handling solutions or automation for molecular biology workflows.
• Familiarity with performing large-scale pooled CRISPR screens.
• Proficiency in flow cytometry or cell sorting for single cell sample preparation.
• Experience with software for data analysis and visualization. Familiarity with analyzing data using Python, R, or another high-level programming language is a plus.

The base salary range for this position is $87,000 - $114,250. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

About the position

We are seeking a highly skilled and motivated Scientist with a strong background in functional genomics and single-cell sequencing to join the Virtual Cell Initiative at Arc Institute. The initiative aims to create the first foundational model that makes accurate predictions of cellular states and their response to intervention. In this role, you will lead the generation of massive single-cell perturbation datasets across 50+ cancer cell lines to train Virtual Cell models. 

You will be responsible for the end-to-end experimental workflow—from mammalian cell culture and large-scale CRISPR screening to single-cell library preparation and sequencing. Beyond technical execution, this role requires a scientist with exceptional project management capabilities, proficient in organizing complex data streams and adhering to timelines. The successful candidate will thrive within our vibrant team science culture, collaborating daily with other wet lab scientists, automation engineers, and computational biologists. We believe that the most ambitious science is achieved together, and in this highly integrated role, you will bridge the gap between experimental biology and computational innovation. 

About you

• You are passionate about the intersection of high-throughput biology and AI/ML to advance human health.
• You enjoy working collaboratively with others and thrive in a fast-paced, dynamic, team science environment.
• You are committed to scientific rigor, generating high-quality data, and maintaining thorough documentation practices.
• You possess a process-oriented mindset, constantly seeking ways to optimize workflows for efficiency and scalability.
• You are diligent, detail-oriented, and excel at troubleshooting complex experimental pipelines.
• You excel at organization, time management, and task prioritization, and enjoy independently driving multiple projects in parallel.

In this position you will

• Execute large in vitro perturbation screens in diverse cell types to generate high quality single-cell perturbation datasets.
• Work with our interdisciplinary teams to further optimize functional genomics platforms and CRISPR technologies for large-scale data generation.
• Utilize project management systems to track progress and adhere to timelines, and document experimental data on ELN/LIMS in an organized manner.
• Interact cross-functionally with wet lab, computational, and machine learning teams to generate, analyze, and interpret data.
• Present key research findings at internal meetings and seminars, and external conferences.

Requirements

• PhD in Cell Biology, Molecular Biology, Genomics, or another relevant field. 
• 0-3 years of post-PhD experience in academia or industry.
• Extensive experience with large-scale pooled CRISPR screening, preferably with scRNA-seq readouts (e.g. Perturb-seq, CROP-seq).
• Expertise in mammalian cell culture and ability to manage multiple cell lines simultaneously.
• Experience in multi-color flow cytometry.
• Experience with mammalian cell line engineering using transfection, lentivirus production and transduction, and other common approaches.
• Experience with different molecular biology techniques (cloning, PCR, etc).
• Demonstrated ability to work both independently and in a highly collaborative multidisciplinary environment.
• Strong project management skills with the ability to independently plan, execute, and deliver results on time. Experience with using various project management systems, ELN and LIMS (e.g. Asana, Benchling).
• Excellent written and verbal communication skills.

Preferred Qualifications

• Hands-on experience with downstream genomics protocols, especially scRNA-seq (preferably 10X Genomics workflows).
• Experience designing and cloning large pooled CRISPR sgRNA libraries.
• Experience optimizing different CRISPR-Cas9 effector systems, such as CRISPRi and CRISPRa, including vector design and delivery.
• Experience performing FACS-based cell sorting.
• Ability to analyze large datasets using Python, R, or similar tools.
• Familiarity with different NGS technologies (Illumina, Ultima).
• Experience using automation to scale, streamline, and optimize large-scale experiments.

The base salary range for this position is $121,250 - $159,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

About the position

We are seeking a highly skilled and motivated Scientist with a strong background in cellular engineering and stem cell biology to join the Molecular Engineering team within the Genome Engineering Technology Center at the Arc Institute. In this role, you will design, generate, and characterize engineered human pluripotent stem cell (hPSC) lines for arrayed genetic perturbation screens in complex organoid models used to recapitulate and probe human genetics of neurodegenerative disorders. Examples of engineering projects include developing optimized effector systems for gene knockdown and activation that function robustly throughout differentiation, introducing rare coding variants to model disease-associated mutations, and implementing novel genome engineering technologies to expand perturbation capabilities. Through this work, you will play a critical role in the Institute's Alzheimer's Disease Initiative, an ambitious cross-functional effort aimed at identifying and drugging rational therapeutic targets to combat devastating neurodegenerative disorders.

This position is highly collaborative and the candidate will have an unique opportunity to interface with pioneering labs that have developed the fundamental toolbox for genome engineering and functional genomics screens, such as CRISPR nucleases, CRISPRi, CRISPRoff, CRISPRa, and serine or bridge recombinases.

About you

• You are passionate about science and excited about answering questions related to molecular design, genome engineering technology development, and complex human diseases.
• You embrace challenges and often formulate creative solutions to develop new approaches and optimize existing tools to answer complex biological questions.
• You understand the importance of collaboration and thrive when working with a diverse team of scientists.
• You have a deep commitment to data quality while working in a fast-paced environment.
• Your organizational skills enable you to manage multiple concurrent projects, and your curiosity and creativity drive you to continuous learning and innovation.

In this position you will

• Develop and optimize engineered hPSC lines for arrayed genetic perturbation screens in complex organoid models, applying genome engineering strategies tailored to the desired edit and experimental goals.
• Design and implement systematic approaches to identify, benchmark, and optimize effector systems for gene knockdown and activation that function robustly throughout differentiation to disease-relevant cell types.
• Execute clonal isolation, expansion, and comprehensive characterization of engineered cell lines, applying and refining established quality control standards and assays to ensure functionality, stability, and reproducibility across multiple engineering approaches.
• Support the cross-functional execution of arrayed genetic perturbation screens for the Alzheimer’s Disease Initiative at Arc. 
• Serve as a key technical resource for cellular engineering of stem cells, partnering with researchers across Arc's Tech Centers and Core Labs to support a wide range of experimental applications and flexibly implement genome engineering approaches based on key biological questions and downstream requirements.
• Present findings at internal meetings and external conferences, and contribute to scientific publications.
• Stay updated on the latest developments in the fields of genome engineering, stem cell biology, and cellular engineering, actively seeking out opportunities for innovation and technology adoption.

Requirements

• PhD in Molecular Biology, Bioengineering, Genetics, or a related field.
• 0-3 years of post-PhD research experience (industry or academia).
• Experience with genome and cell line engineering in stem cells, leveraging a range of genome engineering strategies (CRISPR-Cas9 knock-in, recombinase systems, base editing, prime editing, etc.) and performing comprehensive characterization including on-target validation, off-target assessment, and functional validation of edited cell lines.
• Experience with and enthusiasm for applying cutting-edge molecular tools to disease modeling and function-based screening, and implementing application-driven iterative, systematic technology maturation.
• A collaborative mindset and enthusiasm for mentoring and working within a cross-functional team.
• Strong project management skills with the ability to plan, execute, and deliver results on time.

Preferred Qualifications

• Experience differentiating hPSCs into neural or immune lineages; microglia differentiation experience highly desirable.
• Experience with transcriptional modulation systems (CRISPRi/a) for functional genomics screens, including effector optimization and performance benchmarking.
• Proficiency with computational tools for analyzing genomics data (Python, R, or similar).
• Experience with LIMS systems, ideally Benchling.

The base salary range for this position is $121,250 - $159,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

About the position

We're looking for a Full Stack Engineer with a backend and internal tools focus to help build the software infrastructure that powers science at Arc. You'll own and develop platforms that Arc's researchers rely on daily, from genomics submission systems to data catalogs to ML tooling, while contributing to public-facing products like the Virtual Cell Challenge. This is a hands-on, cross-functional role where you'll work directly with biologists, bioinformaticians, and ML engineers to understand their workflows and build tools that become essential to how researchers work.

About you

• You thrive at the intersection of engineering and domain expertise, building tools that make complex scientific workflows feel simple.
• You have a sharp eye for inefficiency and don't wait to be told what to build. You proactively seek out friction in workflows, talk to users, and propose solutions.
• You’re comfortable collaborating across disciplines, working with researchers, designers, and other stakeholders to clarify needs, define scope, and build intuitive, elegant tools.
• You’re a strong communicator and a self-directed builder who enjoys taking ownership, iterating quickly, and learning on the fly.
• You care about clarity and craft, writing clean code and building interfaces that balance usability, performance, and simplicity, without over-engineering.

In this position you will

• Own and evolve the Virtual Cell Challenge backend, including authentication, metrics pipelines, and participant analytics
• Build and maintain Arc's internal Genomics platforms, including NGS submission, sample tracking, and QC automation
• Architect and develop an internal Data Catalog for browsing, searching, and interacting with rich datasets across the Virtual Cell Atlas and other research programs
• Build tooling and infrastructure to support Arc's ML engineering workflows such as model registries, experiment tracking, and inference pipelines
• Own backend services for Arc's Imaging platform, supporting microscopy and spatial data workflows
• Collaborate directly with scientists and computational researchers to identify pain points and ship solutions with a product mindset

Requirements

• 4+ years of experience in backend or full-stack engineering roles, with a Bachelor's degree in Computer Science, Biology, Bioinformatics, or a related field
• Proficiency in Python or Node.js and modern API frameworks such as FastAPI, Flask, or Express
• Strong experience with relational databases (PostgreSQL preferred), including schema design, query optimization, and data modeling
• Proficiency with AI-assisted development tools (Claude, Cursor, Copilot, or similar) as a core part of your workflow
• Experience building internal apps and tools for scientific/technical users

Preferred Qualifications

• Experience with scientific data formats and tools (e.g., h5ad/AnnData, pandas, NumPy, scverse ecosystem)
• Familiarity with cloud infrastructure (GCP, AWS, or Azure)
• Experience with CI/CD pipelines, Docker, and containerized deployments
• Familiarity with modern JavaScript/TypeScript and frameworks such as Next.js and React

The base salary range for this position is $133,000 to $165,000. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.