A laboratory at the newly-formed Department of Biomedical Informatics at the Harvard Medical School (HMS) is looking to recruit several postdoctoral fellows interested in pursuing one or more of the following topics in computational biology:
I. Single-Cell Genomics. The fellow will be charged with developing novel statistical approaches to analysis of single-cell genomic data, mathematical modeling of cellular processes, as well as applications of such techniques to studies healthy and diseased tissues. Strong background in statistics, modeling of stochastic processes and multicellular systems is desired.
II. Computational analysis of epigenetic mechanisms disrupted in cancer and other disease-disrupted tissues. The fellow will be responsible for developing and applying computational methods for integrative analysis of genome-wide epigenetic, transcriptional and proteomic data, aiming to identify specific factors and molecular mechanisms underlying misregulation of the epigenetic states in several types of human cancer. The ideal candidate should have strong quantitative background, ample experience with analysis of sequencing assays, and strong interest in cancer biology.
III. Computational analysis of nucleosome organization. The fellow will be part of the central analysis group for the extensive 4D-nucleus consortium project funded by the NIH. The efforts will be focused on development of analysis techniques for the next generation of experimental methods for measuring organization and dynamics of the eukaryotic nucleus that are being developed by the members of the consortia. Experience with analysis of Hi-C and relevant imaging data is strongly preferred.
All of the projects are being conducted in close cooperation with the expert bench-side laboratories, providing an excellent opportunity for collaborative research. The Harvard Medical School and the Department also provides rich scientific environment, with a number of relevant seminar series, invited speakers, and many neighboring laboratories working on related projects. Please see http://pklab.med.harvard.edu/ for additional information about the laboratory.
PhD in Computational Biology, Statistics, Physics or other related discipline is required. A strong record of publications in the field is desired.
How to apply
Please send cover letter, curriculum vitae and contact information for at least two references to Dr. Peter Kharchenko at firstname.lastname@example.org. Applications will be considered until the positions are filled. Please specify which project you are interested in.
The Department of Biomedical Informatics has been recently formed at the Harvard Medical School to lead development of computational and informatics techniques to address pertinent challenges in modern biological sciences and medicine. The Department’s faculty conduct research at the intersection of biomedicine and information sciences, including bioinformatics, functional genomics, translational medicine, and clinical knowledge management. The Department also hosts the Bioinformatics & Integrative Genomics PhD program (sponsored by NHGRI) and the Biomedical Informatics Masters program.
Harvard Medical School is an Equal Opportunity/Affirmative Action Employer.
Women and minorities are especially encouraged to apply.
Additional Postdoctoral Opportunities
A group led by Peter Kharchenko at the Department of Biomedical Informatics of the Harvard Medical School is searching for postdoctoral fellows interested in developing and applying novel statistical, computational and experimental approaches to study challenges posed by cancer biology and development/maintenance of healthy tissues at a single-cell resolution. The research questions are being pursued in close cooperation with expert bench-side laboratories, providing an excellent opportunity for collaborative research. In particular, we are looking for researchers interested in joining our efforts on single-cell atlas of human brain, lung, kidney and other organs as part of the NIH funded BRAIN and HuBMAP consortia. Fellows interested in application of advanced image analysis techniques to study organization of biological tissues are encouraged to apply.
More info at http://pklab.med.harvard.edu/
Areas of Interest: Single-Cell Analysis, Spatial Analysis, Statistics, Cancer, Tissue homeostasis
- Robust knowledge of statistical methods, and probabilistic modeling techniques
- Experience with quantitative analysis of modern biological assays
- We welcome experience in image analysis, graphical models, and advanced machine learning
- A strong interest in conducting collaborative research
- Track record of publications in peer-reviewed journals
How to apply: Please send cover letter, curriculum vitae and contact information for at least two
references to Peter Kharchenko at email@example.com. Applications will be considered until the position is filled.