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We are hiring for two Scientist positions on Arc's Computational Technology Center, each turning large-scale perturbational and single-cell datasets into mechanistic biological insight:
Perturb-seq / functional genomics track — focused on large-scale CRISPR screen and Perturb-seq analysis, contributing to the Virtual Cell Initiative (VCI).
Neurobiology / microglia track — focused on single-cell analysis of microglia and neurodegeneration, contributing to the Alzheimer's Disease Initiative (ADI).
Please indicate which focus area you're applying for in your application.
Situated at the interface of functional genomics, computational biology, and machine learning, successful candidates will analyze and model data from Perturb-seq, single-cell and multi-omic sequencing, lineage tracing, chemogenetic screens, and related high-throughput experimental approaches.
Both roles are highly collaborative, partnering closely with experimental scientists, bioinformatics infrastructure teams, machine learning researchers, and Arc investigators to identify biological mechanisms, nominate targets, and guide the design of future experiments.
You want to understand biological mechanisms and are not satisfied with lists of differentially expressed genes; you want to understand why perturbations produce specific cellular outcomes.
You have deep hands-on experience with single-cell, perturbational, or multi-omic data and are comfortable working with large, messy biological datasets.
You think carefully about experimental design and enjoy collaborating across disciplines: you can discuss gene regulation, cellular identity, and assay design with experimentalists, and data models, statistics, and software with computational colleagues.
You have a solid understanding of existing computational methods and their limitations. When they are insufficient to answer the questions at hand, you can adapt and extend them.
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You are excited by the opportunity to work in a mission-driven, open-science research institute with close ties to Stanford, UCSF, and UC Berkeley.
Conduct tertiary analyses of large-scale Perturb-seq, single-cell sequencing, multi-omic, and functional genomics datasets to identify functional relationships between genes, regulatory programs, and cellular phenotypes.
Depending on your track, this includes work such as e.g. guide assignment, perturbation-effect estimation, and interaction modeling for pooled CRISPR screens, or trajectory and cell-state analysis of microglial state transitions in neurodegeneration.
Partner with experimental teams on iterative study design, analysis, interpretation, and validation, discovering computational insights that translate into testable biological hypotheses.
Work closely with bioinformatics and data infrastructure teams to define clean handoffs from primary and secondary analysis into exploratory and mechanistic modeling.
Contribute to Arc's Virtual Cell and Alzheimer's Disease Initiatives by generating, analyzing, visualizing, and interpreting datasets that fuel predictive models.
Develop reusable analysis notebooks, dashboards, software tools, benchmarks, and data resources that allow Arc scientists to explore complex datasets effectively.
Present findings to internal stakeholders, and contribute to preprints or open-source projects when the opportunity arises or as needed.
Mentor colleagues and interns and contribute to a collaborative, intellectually rigorous team environment.
Background in cell identity, reprogramming, RNA biology, cell engineering, neurobiology, immunology, cancer biology, or complex disease genetics.
Familiarity with dimensionality reduction and gene module analysis techniques in the context of single-cell biology.
Experience in a startup, technology center, research institute, or other highly collaborative environment where scientific direction and technical execution are tightly coupled.
The base salary range for this position is $135,000 to $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.
Arc Institute is a nonprofit research organization focused on advancing biomedical science through technology-driven approaches, operating at the intersection of biology and machine learning.
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