Post-Doctoral Research Fellow, Computational Cancer Biology
Cures Start Here. At Fred Hutchinson Cancer Research Center, home to three Nobel laureates, interdisciplinary teams of world-renowned scientists seek new and innovative ways to prevent, diagnose and treat cancer, HIV/AIDS and other life-threatening diseases. Fred Hutch’s pioneering work in bone marrow transplantation led to the development of immunotherapy, which harnesses the power of the immune system to treat cancer. An independent, nonprofit research institute based in Seattle, Fred Hutch houses the nation’s first cancer prevention research program, as well as the clinical coordinating center of the Women’s Health Initiative and the international headquarters of the HIV Vaccine Trials Network. Careers Start Here.
At Fred Hutch, we believe that the innovation, collaboration, and rigor that result from diversity and inclusion are critical to our mission of eliminating cancer and related diseases. We seek employees who bring different and innovative ways of seeing the world and solving problems. Fred Hutch is in pursuit of becoming an antiracist organization. We are committed to ensuring that all candidates hired share our commitment to diversity, antiracism, and inclusion.
The laboratory of Dr. Gavin Ha has a Post-Doctoral Research Fellow position open in the Computational Biology Program of the Public Health Sciences and Human Biology Divisions. We are seeking a highly motivated individual who is interested in developing and implementing innovative computational and analytical approaches to study the genetics and epigenetics of cancer. Candidates who are excited about large/complex ‘omics’ data analysis of cancer genomes, computational methods development, and “liquid biopsy” research are encouraged to apply. The position has a competitive salary with great benefits.
Dr. Ha is a Prostate Cancer Foundation Young Investigator, V Foundation Scholar, and holds an NCI Transition Career Development Award. His laboratory develops computational approaches to study cancer genomes from tumors and liquid biopsies, such as circulating tumor DNA. See the lab websites for more information: https://gavinhalab.org/.
We work in an interdisciplinary team environment with many local and external experts. All of our projects involve partnering with investigators who have diverse expertise in molecular and experimental biology, cancer biology, and clinical research. Potential projects will be part of collaborations with Dr. Peter Nelson (Director, Prostate Cancer Research Program, Fred Hutch), Dr. Andrew Hsieh (Deputy Director, Bladder Cancer Program, Fred Hutch), and investigators studying other cancers.
Responsibilities
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
- Liquid Biopsies – develop novel approaches to analyze circulating tumor DNA.
- Multi-omic Data integration – study of advanced bladder cancer
- Methods Development for New Technologies – linked-read or long-read genome sequencing of tumors.
- For examples of recent studies, see PMID:29909985, PMID:29109393, PMID:25060187
Qualifications
Applicants must have a PhD 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.
Applicants should have some or all of the following skills and experience:
- 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 cancer genome data analysis is considered a strong asset
- A background in cancer biology (especially in prostate) is considered a strong asset.
- Experience with analyzing sequencing data is considered a strong asset
- Experience with high performance computing environments and cloud computing environments is a plus
- Applicants must have a demonstrated publication track record
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, machine learning to study cancer and genetics
- Analysis of large, complex genome, epigenome, and transcriptome data
To apply, please submit your application with the following:
- A several paragraph statement of research interests
- CV
- Names and email addresses of three references
- Two representative publications or preprints (if available)
A statement describing your commitment and contributions toward greater diversity, equity, inclusion, and anti-racism in your career or that will be made through work at Fred Hutch is requested of all finalists.
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 our Employee Services Center at hrops@fredhutch.org or by calling 206-667-4700.