Post-Doctoral Fellowship in Genetic Epidemiology and Computational Genomics – Memorial Sloan Kettering Cancer Center

Memorial Sloan Kettering Cancer Center (MSK), located in New York City, is one of the world’s premier cancer centers. MSK fosters an outstanding research environment spanning the continuum from basic to translational biomedical science, with vibrant training programs at the graduate and post-doctoral level, exceptional opportunities for multi-disciplinary collaborations, and unique resources to support genetic and computational studies of cancer (e.g., the Robert and Kate Niehaus Center for Inherited Cancer Genomics, Functional Genomics Initiative, and Marie-Josée and Henry R. Kravis Center for Molecular Oncology).

We seek a postdoctoral fellow in genetic epidemiology and computational genomics to join an NIH-funded research group focused on understanding the molecular underpinnings of inherited cancer susceptibility. The fellow will lead an array of analytical studies aimed at identifying functional/causal variants and risk genes at novel susceptibility loci for esophageal adenocarcinoma, a highly lethal cancer, and its precursor lesion Barrett’s esophagus. These studies will incorporate single-cell sequencing, quantitative trait locus mapping, statistical colocalization and enrichment testing, and functional bioinformatics. As an active member of an interdisciplinary research group, the fellow will build relationships with a range of scientific colleagues, publish peer-reviewed work, present at national conferences, and contribute to grant writing.

 Qualifications and attributes of the ideal candidate include:

  • A doctoral degree in biostatistics/bioinformatics, epidemiology, or related quantitative discipline.
  • Peer-reviewed publications in genetic epidemiology, statistical genetics/genomics, or related fields.
  • Interest in applying statistical and computational approaches to understand cancer susceptibility.
  • Strong understanding of quantitative methods, study design, and data analysis and interpretation.
  • Excellent coding skills in R (and/or Python), and experience working on Linux-based clusters.
  • Familiarity with public bioinformatics resources such as Roadmap/ENCODE, GTEx, TCGA.
  • Self-motivated, resourceful, enthusiastic; solid verbal and written communication skills.

Interested applicants should send inquiries and applications to buasm@mskcc.org. Please include C.V., contact information for three references, and brief letter of interest addressed to Dr. Matthew F. Buas.

MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status or any other factor which cannot lawfully be used as a basis for an employment decision.

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