Post-Doctoral Research Fellow - 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. 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.

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 circulating tumor DNA in liquid biopsies. Our goals are to uncover mechanisms of treatment resistance, identify blood-based genetic biomarkers, and translate these findings to 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.

Liquid Biopsy Analysis and Methods Development - develop new computational methodologies for exploiting liquid biopsies to study human diseases
• Prenatal diagnostics and Pregnancy disorders - study of prenatal cell-free DNA to study pregnancy disorders such as preeclampsia, including development of new methodologies for early detection and monitoring
• 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.
• For examples of recent studies, see PMID:39939524; 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 think independently but also enjoy working in a dynamic, collaborative, multidisciplinary team.
• Strong programming experience (R, Python, Matlab, Java, C/C++, Perl or other languages for research).
• Experience with analyzing sequencing data is required.
• Knowledge of cancer biology or prenatal/pregnancy disorders is a strong asset.
• Experience with high performance computing environments and cloud computing environments is a strong asset.
• Applicants must have a demonstrated publication track record.

PREFERRED QUALIFICATIONS:

• Prenatal diagnostics, pregnancy disorders, cancer genomics, liquid biopsies, tumor evolution/heterogeneity.
• Application of agent-based modeling, deep learning, 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).

The annual base salary range for this position is from $80,172 to $95,014, and pay offered will be based on experience and qualifications.

This position may be eligible for relocation assistance.

This position is not eligible for H-1B sponsorship at this time.

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).