Post-Doctoral Research Fellow

Fred Hutchinson Cancer Center • Seattle, WA

10h • Onsite

About The Position

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. We are hiring a Post-Doctoral Research Fellow to provide collaborative and innovative analytic support in the Huang Group at Fred Hutch. The Huang Group’s research is focused on design and analysis of vaccine/monoclonal antibody clinical trials, immunological biomarker studies related to the prevention of infectious diseases, and pharmacokinetics modeling of monoclonal antibodies and their interactions. The applicant should have previous training and research experience in longitudinal data or kinetics modeling of biological processes, preferably using one or more pharmacokinetic modeling software applications. The applicant needs to have relevant educational background and knowledge to assume an effective, collaborative role within an interdisciplinary team in biostatistics, mathematics, immunology, virology, and infectious diseases. Good written and oral communication and organizational skills are essential. Dr. Yunda Huang's faculty profile: https://www.fredhutch.org/en/faculty-lab-directory/huang-yunda.html

Requirements

• PhD degree in Pharmaceutical sciences, Statistics, Biostatistics, Bioinformatics, Mathematics, Computer Science or related field.
• Experience with analysis of longitudinal data sets.
• Highest scientific rigor and integrity.
• Strong oral and written communication and critical thinking skills.
• Ability to work independently and within multidisciplinary teams.
• Demonstrated ability to work successfully as part of a diverse team with a commitment to equity and inclusion.

Nice To Haves

• Proficiency in R or Python.
• Experience with survival data analysis.
• Knowledge of a variety of data formats and markup languages (e.g. RMarkdown).
• Experience with modeling software packages, such as Monolix, Phoenix Modeling & Simulation, NONMEM, SAAM II, SimCyp, GastroPlus MATLAB, and R
• Experience with visualization software: Shiny, Javascript, D3.
• Experience with code version control (Git, Github) and containers (Docker).

Responsibilities

• Develop novel multi-compartmental pharmacokinetics modeling approaches and optimal sampling designs of pharmacokinetics studies.
• Conduct data analyses and simulation studies utilizing modern statistical and machine learning algorithms, predictive models, and classification methods to advance infectious disease research.
• Participate in the framing and design of pharmacokinetic and statistical analysis plans.
• Disseminate research output in peer-reviewed scientific journals and conferences.

Benefits

• 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)
• paid parental leave (up to 4 weeks)

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree