ZipRecruiter

Log In

1

Computational Systems Biology Jobs (NOW HIRING)

Bayer

$106K - $159K/yr

PhD in Computational Biology, Bioinformatics, Systems Biology, Biostatistics, Computer Science, or related field; or MSc with substantial relevant experience. Hands-on experience analyzing mass ...

previous page

Showing results 41-60

All JobsComputational Systems Biology Jobs

Computational Systems Biology information

See salary details

$10

$54

$86

How much do computational systems biology jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for computational systems biology in the United States is $54.32, according to ZipRecruiter salary data. Most workers in this role earn between $41.83 and $64.42 per hour, depending on experience, location, and employer.

What is computational systems biology?

Computational systems biology is an interdisciplinary field that uses computational methods, mathematical modeling, and systems theory to understand complex biological systems. It integrates data from genomics, proteomics, and other high-throughput technologies to build models that simulate the behavior of biological networks and pathways. This approach helps researchers predict how biological systems respond to different conditions, design experiments more efficiently, and uncover principles underlying life processes. Computational systems biology is crucial for advancing personalized medicine, drug discovery, and our overall understanding of biology.

What is the difference between Computational Systems Biology vs Bioinformatics Specialist?

AspectComputational Systems BiologyBioinformatics Specialist
Required CredentialsPhD or Master’s in Computational Biology, Bioinformatics, or related fieldsBachelor’s or Master’s in Bioinformatics, Computer Science, or related fields
Work EnvironmentResearch labs, academic institutions, biotech companiesHealthcare, research institutions, biotech firms
Industry UsageAcademic research, drug discovery, systems-level analysisGenomic data analysis, sequence alignment, data management

Computational Systems Biology and Bioinformatics Specialist roles often overlap but differ in focus. Computational Systems Biology emphasizes modeling biological systems at a systems level, while Bioinformatics Specialists focus on analyzing biological data, especially genomic sequences. Both roles require strong computational skills and are vital in biotech and research industries.

What are some common interdisciplinary collaborations for professionals in computational systems biology?

Professionals in Computational Systems Biology frequently collaborate with experts in fields such as molecular biology, bioinformatics, computer science, and clinical research. These collaborations are essential for integrating experimental data, developing computational models, and interpreting complex biological systems. Teamwork often involves regular meetings, data-sharing platforms, and joint project planning to ensure that computational insights are effectively translated into biological understanding and practical applications. Such a collaborative environment fosters skill development and opens pathways for career advancement within both research and industry settings.

What are the key skills and qualifications needed to thrive as a computational systems biologist, and why are they important?

To thrive as a Computational Systems Biologist, you need a strong background in biology, mathematics, and computer science, often supported by an advanced degree in a related field. Expertise in programming languages (such as Python or R), familiarity with bioinformatics tools, and experience using systems biology modeling platforms (like MATLAB or CellDesigner) are commonly required. Strong analytical thinking, problem-solving abilities, and effective collaboration skills set top performers apart in this interdisciplinary domain. These skills are crucial for understanding complex biological systems, developing predictive models, and advancing research in biomedical science.
More about Computational Systems Biology jobs
What cities are hiring for Computational Systems Biology jobs? Cities with the most Computational Systems Biology job openings:
What states have the most Computational Systems Biology jobs? States with the most job openings for Computational Systems Biology jobs include:
What job categories do people searching Computational Systems Biology jobs look for? The top searched job categories for Computational Systems Biology jobs are:
Computational Systems Biology jobs near you
Infographic showing various Computational Systems Biology job openings in the United States as of August 2026, with employment types broken down into 85% Full Time, 9% Part Time, 5% Contract, and 1% Nights. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $112,983 per year, or $54.3 per hour.

Scientist, Computational Biology

Arc Institute

Palo Alto, CA • On-site

Full-time

Posted 6 days ago

Job description

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 hiring for two Scientist positions on Arc's Computational Technology Center, each turning large-scale perturbational and single-cell datasets into mechanistic biological insight:
  1. Perturb-seq / functional genomics track - focused on large-scale CRISPR screen and Perturb-seq analysis, contributing to the Virtual Cell Initiative (VCI).
  2. 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.
About you
  • 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.
  • 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.
In this position you will
  • 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.
Requirements
  • PhD in computational biology, bioinformatics, genomics, systems biology, machine learning, computer science, molecular biology, or a related field, with 0-4 years of postdoctoral or professional research experience.
  • Demonstrated track record of deriving biological insight from large-scale single-cell, perturbational, or multi-omic datasets.
  • Hands-on experience with single-cell, perturbational, or multi-omic data, e.g. single-cell RNA-seq, Perturb-seq or CRISPR screens, single-cell ATAC-seq or multiome, including tertiary analysis, such as gene regulatory network inference, perturbation-effect or interaction modeling.
  • Expertise in at least one of the following:
    • (a) Perturb-seq / CRISPR screen analysis at scale, including guide assignment, perturbation-effect estimation, interaction modeling, batch correction, and interpretation of pooled genetic screens; or
    • (b) Single-cell analysis of microglia, in the context of neurodegeneration and Alzheimer's disease biology.
  • Python proficiency, with experience using modern scientific computing and data analysis ecosystems.
  • Familiarity with reproducible computational workflows, version control, and high-performance or cloud computing environments.
  • Biological intuition and the ability to collaborate effectively with experimental scientists.
  • Excellent written and verbal communication skills, with a track record of publications, preprints, open-source tools, or other scientific outputs.
  • Ability to work in a fast-paced, ambitious, interdisciplinary research environment.
  • Work a minimum of 3 days onsite in our Palo Alto office.
Preferred qualifications
  • 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.

Apply