Scientist, Bioinformatics

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.

• Join a new type of research institute. Work within an organization that combines the speed, focus, and technical execution of a startup with the intellectual depth and scientific rigor of a world-class academic research environment. Arc was built to remove many of the traditional constraints on ambitious science, enabling researchers and technologists to pursue bold, long-term questions with uncommon institutional support.
• Work at the frontier of computational biology. As part of the Computational Technology Center, you will help develop, scale, and deploy bioinformatics methods across some of the most exciting areas in modern biology, including single-cell genomics, multi-omics, Perturb-seq, spatial transcriptomics, CRISPR screens, and imaging-based technologies. Your work will not be limited to one project or dataset; you will contribute to reusable computational capabilities that can accelerate many scientific programs across the institute.
• Make a direct impact on high-risk, high-reward science. This role sits at the interface of computational method development, production-scale data analysis, and experimental discovery. You will help turn complex biological data into actionable insights for scientists studying fundamental mechanisms of human disease, including cancer, neurodegeneration, and immune dysfunction.
• Collaborate with exceptional scientists and technologists. You will work closely with experimentalists, computational scientists, technology center teams, and Core Investigators across Arc and its partner institutions: Stanford, UCSF, and UC Berkeley. This is an opportunity to be part of a highly collaborative environment where bioinformatics is not a downstream service, but a central driver of discovery.
• Build systems that matter. Beyond analyzing data, you will help create robust, tested, documented, and scalable pipelines that support production-level research. Your work will improve how data flows from sequencing instruments to biological interpretation, helping teams move faster while maintaining scientific rigor and reproducibility.
• Grow with an ambitious institute. Arc is still early in its trajectory, which means this role offers unusual opportunities for ownership, influence, and career growth. You will help shape bioinformatics practices, computational standards, and cross-team workflows as the institute expands.
• Do science in a culture built for curiosity and collaboration. Arc aims to create an environment where excellent science, technical rigor, generosity, and intellectual ambition reinforce one another. For a bioinformatics scientist who enjoys both deep technical work and close scientific partnership, this role offers the chance to help define how modern computational biology can be practiced at institutional scale.

The Arc Institute is seeking a Bioinformatics Scientist to join the Bioinformatics team within the Computational Technology Center. The successful candidate will play a crucial role in advancing the state-of-the-art in bioinformatics by developing, implementing, and applying computational approaches to high-throughput biological datasets. In this role, the Bioinformatics Scientist will contribute to major initiatives across the institute, working closely with experimentalists, technologists, and computational scientists to analyze complex sequencing and multi-omics data, support production-scale research efforts, and help translate data into actionable biological insights. This position offers the opportunity to support researchers across diverse scientific programs while helping build reliable, scalable, and reproducible bioinformatics workflows that accelerate discovery and enable Arc’s mission to better understand and treat complex human diseases.

• You are passionate about science and excited about answering biological questions related to complex human diseases.
• You are known for your ability to analyze complex datasets and work effectively in a multidisciplinary team. 
• Your organizational skills enable you to manage multiple concurrent projects, and your curiosity and creativity drive you to continuous learning and innovation.
• You possess outstanding scientific coding and software engineering skills.

• Implement, test, and maintain state-of-the-art analysis pipelines for various high-throughput projects using best software engineering practices.
• Run the production pipelines for large-scale production datasets and provide quality assurance to experimentalists and technologists.
• Analyze large-scale sequencing datasets (single-cell RNA-seq, epigenomics, multi-omics, Perturb-seq, spatial transcriptomics), public and generated in-house.
• Process sequencing data as they come off instruments, monitoring runs, producing actionable results, and troubleshooting issues to ensure timely delivery.
• Communicate analysis results to experimental and computational scientists.
• Partner with experimentalists to troubleshoot analyses and help interpret pipeline outputs.
• Manage code repositories on GitHub, document workflows, and maintain computational environments to ensure pipeline reliability. Support multiple concurrent projects across different Technology Centers, requiring effective context-switching.

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, or related quantitative field.
• 1–2 years of post-Ph.D. experience in bioinformatics, computational biology, genomics, or related analysis of high-throughput sequencing datasets in an academic, biotech, pharmaceutical, or research institute setting.
• Hands-on experience analyzing single-cell omics data, including scRNA-seq, scATAC-seq, and Perturb-seq, encompassing end-to-end workflows from raw data processing (alignment, quantification and QC) through dimensionality reduction, clustering, cell type annotation, trajectory inference, and differential expression analysis.
• Hands-on experience leveraging AI-assisted development tools (e.g. Claude Code, GitHub Copilot, OpenAI Codex) to accelerate software development workflows, including automated code generation, refactoring, and review; and applying AI-assisted data analysis techniques to extract insights from large or complex datasets.
• Demonstrated ability to collaborate effectively with wet-lab scientists, translating biological questions into computational analyses, communicating quantitative results to non-computational audiences, and iterating on analytical approaches in response to experimental findings; experience participating in cross-functional research teams spanning experimental design, data generation, and computational interpretation.
• High competency with Python, git/GitHub, and Linux.
• Strong statistical, mathematical, and data science skills.

• Familiarity with CRISPR screen analysis, including Perturb-seq experimental design considerations, guide assignment, and perturbation effect modeling.
• Scientific background in one or more disease-relevant areas, including neurodegeneration, cancer biology, or immunology.
• Experience with cloud computing platforms (particularly GCP) for running production-scale pipelines.
• Experience contributing to or maintaining open-source bioinformatics software, including writing tests, documentation, and versioned releases.
• Comfort working with large imaging-based datasets or familiarity with image analysis pipelines is a plus.

The base salary range for this position is $$135,000-$186,500. 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.