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Computational Immunology Jobs (NOW HIRING)

The University of Chicago

Staff Scientist

Chicago, IL · On-site +1

The role emphasizes exploratory work at the intersection of immunology and AI. The Staff Scientist will work in a collaborative environment with computational and experimental investigators in the ...

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How much do computational immunology jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for computational immunology in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

What is computational immunology?

A Computational Immunology job involves using data science, bioinformatics, and mathematical modeling to study the immune system. Professionals in this field analyze large biological datasets, develop algorithms, and create simulations to understand immune responses and disease mechanisms. They work in academia, biotechnology, and pharmaceutical industries, contributing to vaccine development, immunotherapy, and precision medicine. The role requires expertise in immunology, programming, and statistical analysis.

What does a computational immunology professional do?

A professional in Computational Immunology typically spends their day designing and executing computational analyses of immunological data, such as sequencing or single-cell datasets. They often collaborate with experimental immunologists, bioinformaticians, and clinicians to interpret results and guide research directions. Tasks might include developing predictive models, visualizing complex immune system interactions, and reporting findings in team meetings or publications. Due to the interdisciplinary nature of the work, strong communication and adaptability are essential, as projects often evolve quickly with new scientific discoveries.

What are the key skills and qualifications needed to thrive in computational immunology?

To thrive in Computational Immunology, you need a strong background in immunology, bioinformatics, and computer science, typically supported by an advanced degree (MS/PhD) in these fields. Proficiency with programming languages such as Python or R, experience with high-throughput data analysis, and familiarity with platforms like Bioconductor or Cytoscape are highly valued. Excellent problem-solving, teamwork, and communication skills help professionals interpret complex data and present findings to multidisciplinary teams. These combined technical and soft skills are essential for advancing research in immunological mechanisms and driving innovation in areas such as vaccine development or immunotherapy.

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Computational Immunology jobs near you
Infographic showing various Computational Immunology job openings in the United States as of August 2026, with employment types broken down into 71% Full Time, 26% Part Time, 1% Temporary, and 2% Contract. Highlights an 69% Physical, 2% Hybrid, and 29% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Computational Biologist

Odyssey Therapeutics, Inc.

Boston, MA • On-site

$120K - $180K/yr

Full-time

Re-posted 5 days ago

Job description

Odyssey Therapeutics is propelling drug development beyond what is now possible to deliver medicines that address critical needs of patients with inflammatory and immunology diseases. We achieve unprecedented speed and efficiency by bringing together a target-centric approach, a toolbox of cutting-edge technologies, and a team of accomplished, world-class drug hunters. By reimagining the drug development process, we are creating a deep and broad drug pipeline that holds the potential to transform human health.
The opportunity:
Odyssey Therapeutics is seeking a Computational Biologist to support target discovery, translational biology, biomarker development, and clinical data analysis across our portfolio of autoimmune and inflammatory disease programs.
This role will work closely with Discovery Biology, Translational Medicine, Clinical Development, and external collaborators to analyze and integrate genomic, transcriptomic, and clinical datasets to generate actionable biological insights that support therapeutic hypothesis generation, patient stratification, and clinical development strategies.
Your primary objectives will be:
  • Analyze internal and publicly available omics datasets to support target discovery, translational research, and therapeutic hypothesis generation.
  • Develop, maintain, and optimize robust bioinformatics pipelines for the analysis of multi-omics datasets.
  • Analyze GWAS, eQTL, transcriptomic, proteomic, and other human disease datasets to identify disease-relevant pathways, therapeutic targets, and biomarkers.
  • Evaluate clinical and translational datasets to identify biomarkers associated with therapeutic response, resistance, and disease progression.
  • Collaborate closely with Discovery Biology, Chemistry, Translational Medicine, and Clinical Development teams to integrate diverse datasets and generate actionable biological insights.
  • Present scientific findings to cross-functional teams and contribute to internal reports, scientific presentations, publications, and external communications.

About you:
  • Ph.D. (or equivalent experience) in Computational Biology, Bioinformatics, Genetics, Immunology, Systems Biology, or a related discipline.
  • 2+ years of experience developing bioinformatics pipelines and applying computational approaches to immunology and/or drug discovery in an industry or academic setting.
  • Deep expertise in computational biology, bioinformatics, and statistical analysis of large-scale biological datasets.
  • Experience analyzing GWAS, whole-genome sequencing (WGS), and other human genetics datasets.
  • Experience working with large public genomics resources such as GEO, ArrayExpress, UK Biobank, All of Us, Open Targets, FinnGen, or similar repositories.
  • Demonstrated expertise in developing pipelines for bulk and single-cell omics technologies, including RNA-seq, scRNA-seq, CITE-seq, ATAC-seq, ChIP-seq, WGS, and WES.
  • Strong proficiency in R and/or Python, with experience using version control and developing reproducible, standardized analysis workflows.
  • Ability to rapidly learn and apply new computational methods and emerging omics technologies.
  • Broad understanding of molecular biology, cell biology, biochemistry, and translational research.
  • Familiarity with autoimmune, inflammatory, or immune-mediated diseases.
  • Experience managing and analyzing large, complex datasets across multiple research programs.
  • Proven ability to work collaboratively with computational scientists, biologists, chemists, and cross-functional project teams.
  • Strong scientific communication skills, with the ability to independently perform analyses and clearly communicate findings to both computational and non-computational audiences.
  • Demonstrated scientific contributions to computational biology and drug discovery through publications, presentations, or other impactful research.
  • Creative, scientifically rigorous, and motivated to solve challenging biological problems in a collaborative environment.
  • Experience supporting translational medicine, biomarker discovery, or clinical development programs is preferred.
  • Experience integrating multi-modal omics datasets and applying AI or machine learning approaches to biological data analysis is preferred.

Pay Range Disclosure Statement:
The ranges provided are based on what we believe are reasonable estimate for the base salary pay ranges for this job at the time of posting. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.
The pay range for this role is:
120,000 - 180,000 USD per year (Boston, MA)

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