Post-Doctoral Research Fellow - Biostatistics

the opportunity to contribute to one or more of the following priority areas: Immune surrogate biomarker development, with an emphasis on modeling longitudinal immune responses and linking them to clinical outcomes; Addressing challenges of complex non-compliance in cancer screening trials; and Efficient design and analysis strategies for multi-cancer detection (MCD) trials.

In addition to advancing novel methods, the fellow will have opportunities to analyze large-scale, high-impact medical studies in cancer and infectious disease prevention.

Responsibilities also include: Attending lab meetings and regular meetings with PI Writing/editing/drafting/contributing towards publications and presentations Collaborate with multidisciplinary research teams including statisticians, epidemiologists, laboratory scientists, and clinicians to translate statistical findings into biological and clinical insights.

Contribute to methodological research in areas such as surrogate biomarker evaluation, causal inference, and trial design, leading to publication in peer-reviewed journals.

Stay current with emerging statistical methods and relevant biomedical literature to inform ongoing research and foster innovation. Present research findings through publications, conference presentations, and internal seminars.

Support grant proposals and progress reports by contributing statistical expertise and analysis results if needed. Contribute to methodological research in areas such as immune biomarker evaluation, causal inference, and clinical trial design.

Demonstrate commitment to scientific integrity, collaboration, and continuous professional growth.

Qualifications

MINIMUM

QUALIFICATIONS: PhD degree (or equivalent) in Biostatistics, Statistics, Mathematics, Computer Science or related.

PREFERRED

QUALIFICATIONS: Demonstrated expertise in one or more of the following areas: survival analysis, longitudinal data analysis, two-phase sampling techniques, methods for handling missing data, causal inference, measurement error models, and methods for biomarker evaluation.

Proficiency in R or Python. Experience in C/C++ a plus. Highest scientific rigor and integrity.

Strong oral and written communication and critical thinking skills.

Ability to work independently and within multidisciplinary teams. The annual base salary range for this position is from $80,172 to $95,014, and pay offered will be based on experience and qualifications.

This position may be eligible for relocation assistance. Although Fred Hutch is not sponsoring most H-1B visas at this time, candidates who already hold an H-1B sponsored by another organization and are currently in the U.S. may be eligible for this position.

Benefits include medical/vision, dental, flexible spending accounts, life, disability, retirement, family life support, employee assistance program, onsite health clinic, income-based child care subsidy, tuition reimbursement, paid vacation (22 days per year), paid sick leave (up to 30 calendar days per occurrence of a qualifying reason), paid holidays (13 days per year), and paid parental leave (up to 4 weeks).