Post-Doctoral Research Fellow - Cancer Genomics

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.

The laboratory of Dr. Gavin Ha (https://gavinhalab.org) has a Post-Doctoral Research Fellow position open in the Herbold Computational Biology Program of the Public Health Sciences and Human Biology Divisions. We are seeking a highly motivated individual who will bring a deep understanding of cancer biology to our computational team. Candidates who are excited about new laboratory and computational methods to study large/complex 'omics' data of cancer genomes and liquid biopsy research are encouraged to apply. The position has a competitive salary and great benefits.

The Ha Lab develops computational approaches to study cancer genomes from tumors and liquid biopsies, such as circulating tumor DNA. Their goals are to uncover mechanisms of treatment resistance, to identify blood-based genetic biomarkers, and to translate these findings to help improve clinical applications. The lab is supported by the National Institutes of Health (NIH) and DoD/CDMRP, including receiving funding from the NIH Director's New Innovator Award, the Prostate Cancer Foundation, and the V Foundation.

We work in an interdisciplinary team environment with many local and external experts. All our projects involve partnering with investigators who have diverse expertise in molecular and experimental biology, cancer biology, and clinical research. The successful candidate will have the opportunity to work on transformative and leading-edge research problems in cancer research:

Cancer Genome Analysis - study tumor evolution, non-coding genome alterations, genome rearrangements and chromatin organization, cell plasticity, metastatic disease
• Multi-omic Data Integration -using genome, transcriptome, methylome, and chromatin/epigenetic data modalities to study cancer subtypes, phenotypes, heterogeneity, and resistance to therapy.
• Liquid Biopsy Analysis and Methods Development - develop new computational methodologies for exploiting liquid biopsies to study cancer and to advance precision oncology
• For examples of recent studies, see PMID:29909985; PMID:29109393; PMID:25060187; PMID: 36399432; PMID: 36463275; PMID: 38598634; See the lab website for more details https://GavinHaLab.org/

MINIMUM QUALIFICATIONS:

• Applicants must have a PhD and/or MD (or equivalent) with training in one of these disciplines: Computational biology, bioinformatics, computer science, data science, statistics, computer/electrical engineering, physics, or other related fields.
• Work well in team environments, have strong communication/organization skills and is detail-oriented
• Highly motivated individual who thinks independently but also enjoys working in a dynamic, collaborative, multidisciplinary team
• Strong programming experience (R, Python, Matlab, Java, C/C++, Perl or other languages for research)
• Experience with cancer biology and cancer data analysis
• Applicants must have a demonstrated publication track record

PREFERRED QUALIFICATIONS:

• Experience with high performance computing environments and cloud computing environments is a strong asset
• Experience with analyzing genome sequencing data is considered a strong asset
• Candidates with strong interest and/or expertise in any of these research areas are highly encouraged to apply:
  • Cancer genomics, liquid biopsies, tumor evolution/heterogeneity
  • Application of statistical modeling, algorithm design, and machine learning to study cancer and genetics
  • Interpretation of data generated from large, complex genome, epigenome, and transcriptome data

To apply, please submit your application with the following:

• Cover letter with a statement of research accomplishments and interests
• Curriculum vitae
• Two representative publications or preprints (if available)

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 $77,976 to $150,000 and pay offered will be based on experience and qualifications. This position may be eligible for relocation assistance.

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, 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).