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Staff Scientist - Cancer Genomics and Data Science

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Seattle, WA

Employer:  Fred Hutchinson Cancer Center
Job Type:  Full Time

Description

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
  • Experience and expertise with programming languages and environments such as R, Python, others.
  • Experience and expertise with bench laboratory methods/techniques in including nucleic acid extraction; construction of NextGen sequencing libraries; PCR; cell culture; cell transfection; cell growth and apoptosis assays.
  • Publications of peer reviewed articles in the field of genomics, genetics, cell engineering, or developmental biology
  • A minimum of 5 years of experience in molecular biology, developmental biology, tissue engineering, genetics, epigenetics, computational genomics or related fields

PREFERRED QUALIFICATIONS:
  • Experience with histopathology and spatial transcriptomics including wet-bench methods for cell and tissue processing.
  • Experience with genome editing technologies such as CRISPR/Cas9
  • Experience managing mouse colonies including genotyping and breeding
  • Experience analyzing various omics datatypes such as RNAseq, HiC data, whole genome sequencing/whole exome sequencing;
  • Experience in technical and regulatory aspects of developing and implementing large-scale genomic data management.
  • Teaching experience in related fields.
  • Expertise in literature review and interpretation of (epi)genomics data.
  • Experience in writing research grant applications and scientific manuscripts

A statement describing your commitment and contributions toward greater diversity, equity, inclusion, and antiracism in your career or that will be made through your work at Fred Hutch is requested of all finalists.

The annual base salary range for this position is from $82,123 to $185,000 and pay offered will be based on experience and qualifications. 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), paid parental leave (up to 4 weeks), and partially paid sabbatical leave (up to 12 months for professor track faculty, up to 6 months for other scientific staff).

Our Commitment to Diversity

We are proud to be an Equal Employment Opportunity (EEO) and Vietnam Era Veterans Readjustment Assistance Act (VEVRAA) Employer. We are committed to cultivating a workplace in which diverse perspectives and experiences are welcomed and respected. We do not discriminate on the basis of race, color, religion, creed, ancestry, national origin, sex, age, disability (physical or mental), marital or veteran status, genetic information, sexual orientation, gender identity, political ideology, or membership in any other legally protected class. We are an Affirmative Action employer. We encourage individuals with diverse backgrounds to apply and desire priority referrals of protected veterans. If due to a disability you need assistance/and or a reasonable accommodation during the application or recruiting process, please send a request to Human Resources at hrops@fredhutch.org or by calling 206-667-4700.
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