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Post-Doctoral Research Fellow

Job in Seattle, King County, Washington, 98102, USA
Listing for: Fred Hutchinson Cancer Research Center
Full Time position
Listed on 2026-09-10
Job specializations:
  • Research/Development
    Research Scientist, Clinical Research, Data Scientist
Job Description & How to Apply Below

Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington.

With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world’s leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states.

Together, our fully integrated research and clinical care teams seek to discover new cures to the world’s deadliest diseases and make life beyond cancer a reality.

At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems.

Post-Doctoral Research Fellow position to study the evolutionary dynamics of B cell affinity maturation. The goal of our project is to use phylogenetic and statistical methods to understand how evolutionary forces shape B cell receptor evolution during affinity maturation, and to test biological hypotheses about this process directly in human B cell repertoire data. Affinity maturation is the process by which B cells accumulate mutations and are selected for improved antigen binding, ultimately producing the antibodies that protect us from infection.

Understanding this process in detail is important both for basic research, such as probing the origins of autoimmune disease, and for translational work, such as designing vaccines that elicit specific immune responses.

We are motivated to:

  • Test biological hypotheses about affinity maturation directly against human B cell repertoire data
  • Develop and apply phylogenetic and statistical methods, building on recent advances in modeling somatic hypermutation and selection, to extract this information from large-scale repertoire sequencing data
  • Collaborate closely with statisticians and immunologists to connect these evolutionary models to mechanistic and clinically relevant questions.

The ideal candidate for this project would have experience with phylogenetics, population genetics, or another evolutionary framework, as well as experience with statistical modeling and computer programming. However, we welcome applications from candidates with less statistical or computational expertise but a deep desire to expand their skills in this area. We hope applicants will want to improve their coding abilities through clean coding practices, code review, and a modern development workflow.

The ideal candidate would also be motivated to improve biological understanding through computation, and so would be enthusiastic about working closely with our collaborators in statistics and immunology.

You can find out more about our group by visiting:

We will work together to develop and apply phylogenetic and statistical methods for analyzing B cell receptor lineages, test hypotheses about affinity maturation using existing and newly collected repertoire datasets, write software implementing these methods, and write papers describing the results. You’ll have the opportunity to work with a broad range of leading researchers, including collaborators with expertise in modeling B cell repertoire dynamics and repertoire data collection.

Minimum qualifications:

  • Ph.D. in biology, computer science, math, or another relevant area.
  • Solid foundation in phylogenetics, population genetics, or another challenging evolutionary or statistical estimation problem.
  • Computer programming experience.
  • Clear ability to perform independent research.

The annual base salary range for this position is from…

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