Job Information
Harvard University Postdoctoral Research Position in High-Dimensional Statistics/Computational Biology in Cambridge, Massachusetts
Details
Title Postdoctoral Research Position in High-Dimensional Statistics/Computational Biology
School Harvard T.H. Chan School of Public Health
Department/Area Biostatistics
Position Description
We are seeking a candidate with expertise in computational biology, machine learning, and/or high-dimensional statistics to work as a postdoctoral research fellow in the Department of Biostatistics at Harvard T.H. Chan School of Public Health. Potential duties and responsibilities involve (i) identifying, formulating, and solving important theoretical or computational challenges arising from emerging single-cell technologies such as single-cell multiomics and spatial transcriptomics; (ii) analyzing single-cell omics data and software development; (iii) writing scientific articles and research proposals. The successful candidate will work with Dr. Rong Ma on computational or theoretical research projects surrounding integrative single-cell omics analysis, manifold learning, and high-dimensional statistics.
Basic Qualifications
Ph.D. in applied math, biostatistics, computer sciences, computational biology, statistics, system biology, or related fields. Strong quantitative (computational or theoretical) research background. Knowledge of single-cell sequencing, differential geometry, or random matrix theory is encouraged but not required.
Additional Qualifications
Special Instructions
Contact Information
Trevor Bierig
Contact Email tbierig@hsph.harvard.edu
Equal Opportunity Employer
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.
Minimum Number of References Required 2
Maximum Number of References Allowed 4
Keywords
Supplemental Questions