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Liver Cancer, Computational Biology, Multi-Omics Data

National Cancer Institute, Bethesda, MD and surrounding area

Position Description:

The NCI CCR Liver Cancer Program (https://ccr.cancer.gov/liver-cancer-program) seeks applications from qualified computational postdoctoral candidates to fill a position in cancer genomics. Applicants to this intramural program should have a background in cancer genomics, computational biology, and/or bioinformatics with an interest in data science.

The NCI CCR Liver Cancer Program is an interactive and multidisciplinary collaborative team fostering liver cancer care and research. Through innovative laboratory studies and promising clinical applications, such as molecular subgrouping of patients and biomarker-guided molecularly targeted therapies, our team aims to improve early detection, diagnosis, prognosis, treatment and outcome of patients with liver disease and cancer. The team builds and uses knowledge sources containing clinical, -omic and in vitro assay data to bridge preclinical research and clinical assessments to find new putative targets for liver cancer. A major project currently underway, NCI-CLARITY, is a translational science network of liver cancer clinical trial data, accompanying biospecimens and correlative laboratory data to determine why immunotherapy is effective in certain patients but not in others and to use this information to develop novel therapies.

Candidates with a solid understanding in the next-generation, omics analysis and integration of multiple data sources (e.g. single-cell RNA sequencing, transcriptomics, whole-genome sequencing), data cleaning/processing/harmonization, machine learning and database management, are preferred. Experience with various types of data sets as listed above is preferred. Although the team is highly collaborative in nature, the candidate’s pursuit of original research directions is also strongly encouraged.
CCR offers fellows access to cutting-edge technologies and cores, one of the world’s most powerful high performance computing systems (Biowulf), a highly collaborative scientific and computational research environment, awards and research forums to recognize outstanding postdocs, continuous scientific symposia and lectures featuring leading researchers, a strong commitment to translational research, and a vibrant clinical research program housed in the world’s largest dedicated research hospital, the NIH Clinical Center.

Core Responsibilities:
The successful candidate will work as part of a multidisciplinary team of innovative scientists to examine how big omic data analysis can aid in the discovery of tumor classes, biological relationships, response to treatments and translation to patient benefit. The fellow is expected to use state-of-the-art modeling and machine learning to identify aforementioned relevant associations and to support clinical decision-making. The fellow will work closely with scientists, clinicians and bioinformaticians to interpret findings and identify areas that require further investigation. The fellow will present results to the team and to the wider scientific community, draft manuscripts and publish results in peer-reviewed journals, and develop and implement novel approaches when standard approaches are not sufficient.

Stipends/Benefits:
Annual stipends are provided and are based on the NIH Postdoctoral Intramural Research Training Award and Visiting Fellow scale; health insurance benefits are available. The position is renewable for up to five years.

Qualifications:

The ideal candidate should possess a doctoral degree or equivalent in bioinformatics, clinical informatics, biomedical informatics or a related field and have demonstrated hands-on experience in leading the analysis of a large (multiple hundreds or greater) cohort data set. The candidate should have demonstrated experience in organizing, cleaning, and harmonizing large data sets, as well as in applying robust statistical methods, including multivariable analyses, machine learning, etc. with a strong record of scientific achievement through peer-reviewed publications. Knowledge of R and/or Python is required, and basic knowledge and understanding of clinical and biological interpretation of molecular data (e.g., -omics, assay screening data, etc.) is preferred along with the desire to acquire new skills as required for research studies.

The selected candidate should be self-motivated, driven, thorough and careful with the ability to multitask, think independently and work in a highly creative, interactive and fast-paced environment alongside a diverse and dynamic multidisciplinary team. They also will be expected to be highly productive, have a strong work ethic and an intellectual commitment to cancer research. Proficient communication in both spoken and written English is required, and excellent interpersonal and organizational skills are highly desired. The selected candidate will keep accurate and complete records of all scientific experiments according to established procedures and ensure that these records and raw data are properly retained.

To Apply:

Please submit (via email) a cover letter describing your career goals and interest in the position, including a research summary (one to two pages), a current curriculum vitae with a complete bibliography, and the names of and contact information for at least three references to Anuradha Budhu, PhD at budhua@mail.nih.gov.
The review of applications will begin immediately and will continue until the position is filled.

The NIH is dedicated to building a diverse community in its training and employment programs and encourages the application and nomination of qualified women, minorities, and individuals with disabilities.