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How much do computational biology co op jobs pay per year?

As of Aug 14, 2026, the average yearly pay for computational biology co op in the United States is $93,988.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,500.00 and $117,000.00 per year, depending on experience, location, and employer.

What kind of projects or tasks can I expect to work on as a computational biology co op?

As a Computational Biology Co Op, you will often assist with processing and analyzing large biological datasets, developing or optimizing algorithms, and performing statistical analyses on experimental results. You may work with teams of biologists, data scientists, and software engineers to explore research questions, interpret data, or help automate routine workflows. Typical tasks can include organizing genomic or proteomic data, running simulations, and preparing reports or visualizations for team meetings. This hands-on experience not only helps you strengthen technical skills but also exposes you to the collaborative problem-solving that drives scientific discovery.

What is a computational biology co op?

A Computational Biology Co-Op is a temporary, structured work opportunity for students or early-career professionals to gain hands-on experience in applying computational techniques to biological research. Responsibilities may include analyzing biological datasets, developing algorithms, and collaborating with scientists on research projects. Co-Ops typically work in academia, biotech, or pharmaceutical industries, applying computational tools to genomics, structural biology, or drug discovery. The role helps bridge the gap between biology and data science, equipping participants with valuable industry skills.

What are the key skills and qualifications needed to thrive in the computational biology co op position?

To thrive as a Computational Biology Co Op, you need a strong background in biology, mathematics, and computer science, often supported by coursework or previous laboratory experience. Familiarity with programming languages such as Python or R, as well as experience with bioinformatics tools and databases, is typically expected. Attention to detail, effective communication, and the ability to work collaboratively with cross-disciplinary teams are valuable soft skills. These skills are crucial for effectively analyzing complex biological data and contributing to ongoing research projects in a dynamic environment.

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Computational Biology Co Op jobs near you
Infographic showing various Computational Biology Co Op job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $93,988 per year, or $45.2 per hour.

Co-Op, ML Scientist for Biology

Lila Sciences

San Francisco, CA

Full-time

Re-posted 20 days ago

Job description

Your Impact at LILA

Lila is building a platform where AI and automation co-evolve to solve hard problems across scientific domains. Within Life Sciences AI, we are developing autonomous-science capabilities for biological systems, spanning multiple biological domains and resolutions, based on multi-modal data and foundation models.

We are seeking a Co-Op, LS AI, ML Scientist for Biology to contribute to cutting-edge research on how to effectively evaluate, guide, and reinforce agentic model behavior in this domain.

This is an opportunity to work alongside Lila scientists on early-stage research in autonomous life science AI. You will help explore reasoning models, evaluation and benchmark datasets, and workflows that connect modern AI methods to real biological questions, gaining hands-on experience in a fast-moving scientific environment.

What You'll Be Building

  • Contribute to ML research on reasoning models for biological discovery and autonomous science.
  • Explore methods to evaluate, guide, and reinforce agentic model behavior in biological domains.
  • Help develop evaluation and benchmark datasets for biological reasoning tasks.
  • Analyze multi-modal biological data to identify useful signals for model evaluation and improvement.
  • Prototype workflows that connect model reasoning, evaluation, and scientific feedback.
  • Communicate findings through code, notebooks, written summaries, and presentations.

What You'll Need to Succeed

  • Currently enrolled in a PhD program in Computer Science, Machine Learning, Computational Biology, Bioengineering, or a related quantitative field.
  • Research experience in machine learning, AI for science, computational biology, or biological data analysis.
  • Strong programming skills in Python and experience with modern ML frameworks such as PyTorch, JAX, or similar tools.
  • Experience working with biological, scientific, or multi-modal datasets.
  • Interest in reasoning models, agentic systems, evaluation methods, or benchmark design.
  • Interest in closed-loop scientific discovery, autonomous labs, or AI systems that interact with experimental feedback.
  • Ability to communicate research findings clearly through code, notebooks, written summaries, and presentations.
  • Comfort working in a collaborative, cross-disciplinary research environment.

Bonus Points For

  • Experience with reasoning models, agentic systems, reinforcement learning, or model evaluation.
  • Experience developing benchmarks, evaluation datasets, or model assessment workflows.
  • Publications, preprints, talks, posters, or workshop presentations in ML, AI for science, computational biology, or related scientific venues.

Apply