Overview

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.

This position is for a Staff Scientist to engage in biomedical studies that apply Artificial Intelligence (AI) approaches and methods with the long-term objective of improving clinical cancer care. The training, project development, and application will be mentored by Dr. Peter Nelson and Dr. Jeff Leek, and members of their research groups. The projects will integrate high dimensional clinical data with outcomes to specific therapeutics to generate patient similars or digital twins. The studies will also develop methodology to produce synthetic control cohorts for comparative assessments against novel therapeutics evaluated in clinical trials. The project will interface with clinical and laboratory investigators involved in the management of prostate cancer, and researchers developing bioinformatics methods that exploit AI technologies in the Fred Hutch Data Science Lab.

The Fred Hutch Data Science Lab is involved in large, education focused initiatives and biomedical research funded by NIH grants. These projects involve delivering training materials to researchers to help catalyze their work in a scalable manner, as well as innovating new methods for understanding or treating disease.

The key areas of emphasis include:

• Primary research using AI and other statistical methods to better personalize treatment of cancer patients from large-scale data.
• Analysis of large-scale clinical, genomic, and molecular datasets.
• Development and evaluation of predictive models and statistical approaches to understand treatment outcomes.
• Integration of diverse data types to identify features associated with therapeutic response, resistance, or toxicity.
• Collaboration with multidisciplinary teams to interpret findings and support translational applications.

Responsibilities

• The research projects and responsibilities for this Staff Scientist position include:
• Conducting research independently as well as contributing to research being done by other team members.
• Assisting in project development, design, and management with administrative staff.
• Developing new statistical models leveraging public and investigator collected high throughput data.
• Writing new R packages or Shiny Apps for implementation of developed methodology.
• Applying AI and ML tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses.
• Develop, refine, and benchmark computational pipelines using statistical modeling, machine learning, and deep learning approaches.
• Conduct analytical validation studies including precision, reproducibility, and specificity.
• Support translational studies in collaboration with clinicians and academic/industry partners.
• Other duties as assigned.

SCOPE OF RESPONSIBILITY:

Level of autonomy:

• This position will report to Dr. Peter Nelson and will collaborate with Dr. Jeff Leek and other members of the project teams as necessary. This candidate will have substantial autonomy to develop and apply tools and methods that incorporate AI and large data sets to understand and predict disease trajectories. The staff scientist will need to conduct most study tasks independently with minimal to modest oversight aside from project steering efforts.

Qualifications

MINIMUM QUALIFICATIONS:

• A PhD and/or MD degree in biomedical sciences, epidemiology, biostatistics, statistics, computer science, machine learning, or another related statistical or computational discipline.
• Creative, thoughtful, and a communicative collaborator
• Familiarity with Python, R, R packages, and RMarkdown.
• Experience with version control using GitHub.
• A willingness to learn new informatics content.
• A careful writer and diligent editor.
• Experience with statistics and machine learning

PREFERRED QUALIFICATIONS:

• Experience with Quarto, Python, and/or other programming languages.
• Experience and interest in data science or informatics education.
• Experience working with clinical data.
• Experience with deep learning applications for biomedical research.
• This position may be eligible for relocation assistance.

The annual base salary range for this position is from $84,406 to $191,755, 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.Fred Hutchinson Cancer Center offers employees a comprehensive benefits package designed to enhance health, well-being, and financial security. Benefits include medical/vision, dental, flexible spending accounts, life, disability, retirement, family life support, employee assistance program, onsite health clinic, tuition reimbursement, paid vacation (22 days per year), paid sick leave (up to 30 calendar days per occurrence of a qualifying reason), paid holidays (up to 13 days per year), and paid parental leave (up to 4 weeks).

Additional Information