Staff Scientist - Cancer Genomics and Data Science

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. These values are grounded in and expressed through the principles of diversity, equity and inclusion. 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. Fred Hutch is in pursuit of becoming an anti-racist organization. We are committed to ensuring that all candidates hired share our commitment to diversity, anti-racism and inclusion.

A Staff Scientist position in the Nelson, Haffner, Li and Ha research groups located in the Human Biology Division and Computational Biology Program is available immediately. We have established a research team working with interdisciplinary collaborators who have expertise in genomics, genetics, pathology, experimental therapeutics, cancer biology, and clinical cancer research. We are seeking a highly motivated individual with experience in applying bench laboratory experimentation and computational and analytical approaches to the study genomics and epigenetics of cancer. Candidates who are excited about driving projects and participating in teams that develop and apply technologies for interrogating cancer genotypes and phenotypes through  bioinformatics, data science, genomics, spatial biology and drug development are encouraged to apply. The position has a competitive salary with excellent benefits.

 

Candidates with strong interest and/or expertise in any of these research areas are highly encouraged to apply

• Developmental biology; cancer genomics, liquid biopsies, tumor evolution/heterogeneity, epigenetics, single-cell omics
• Application of statistical modeling, algorithm design, artificial intelligence and machine learning, explainable AI to study cancer and genetics.
• Analysis of large, complex genome, epigenome or transcriptome data.

This position requires full-time onsite work at our South Lake Union campus in Seattle

Responsibilities

The research projects and responsibilities for this Staff Scientist position include:

• Conduct research independently as well as contribute to research being done by other team members.
• Assist in project development, design and management.
• Participate in the training of undergraduate, graduate and postdoctoral scientists.
• Assist and lead in the assembly of research presentations, manuscripts and grant proposals.
• Conduct ‘wet-bench’ experiments for the assessment and application of new molecular approaches for assessments of cancer genotypes and phenotypes.
• Implement analysis tools/pipelines and interpretation of results for coding and non-coding genome alterations, chromosome copy number alterations, genome rearrangements, 3D structure, and mutational signatures.
• Collaborate with Fred Hutch scientists to refine computational research questions and identify opportunities for implementing novel computational, statistical and machine learning methods to large datasets including genetic and omics data.
• Develop and use computational approaches to analyze circulating tumor DNA from liquid biopsies.
• Develop and use computational approaches to analyze tumor complexity involving single cell and spatial profiling technologies.
• Implement, maintain, and apply the best practices in large-scale data management.

Qualifications

MINIMUM QUALIFICATIONS:

• A PhD and/or MD degree in a biomedical science discipline such as biology, molecular biology, biochemistry, biophysics, computer science, computational biology, biostatistics, biomedical engineering, computer/electrical engineering, or other related fields
• Exp