Two-year, renewable post-doctoral position to develop and implement advanced, innovative statistical approaches for analysis of genetics and genomics data with a focus on complex disease. We are particularly interested in applicants who have experience with methods and analysis of big data, especially genetics and genomics datasets. However, we will consider qualified applicants with experience in other related research areas.
The successful applicant is expected to participate actively both in collaborative research projects and applied methodological research in the area of genetics and genomics of diabetes and Alzheimer’s disease. Participation in large consortium studies provides rich data (phenotype, sequencing and ‘omics) and opportunities for broad networking and collaboration. The position also has potential for teaching opportunities for interested applicants. Successful applicants are highly motivated, dependable, and have excellent communication and writing skills. Strong programming skills are required in R and/or SAS. Additional background with high-level programming languages such as Python, and experience with Linux cluster computing environment is strongly preferred.
The Department of Biostatistics believes that the cultural and social diversity of our faculty, post-docs, staff, and students is vitally important to the distinction and excellence of our research and academic programs. We are eager to have join our ranks a colleague who supports our institutional commitment to ensuring BU is inclusive, equitable, diverse, and a place where all constituents can thrive. The School of Public Health actively seeks to enrich its student, post-doc, and faculty ranks, recognizing that diversity of experience deepens the intellectual endeavor. We seek to embed—within our curricular and co-curricular activities—the principle that pluralism within a learning community is a source of insight and effectiveness.
Candidates should hold a PhD or equivalent doctoral degree in statistics, or biostatistics with strong computing skills. Applications will be considered until the position is filled.
Boston University is an AAU institution with a rich tradition dedicated to inclusion and social justice. We are proud that we were the first American university to award a Ph.D. to a woman and we continue that tradition of educating a diverse and talented student body. The School of Public Health takes the University’s commitment even further with its own detailed plan for fostering a diverse and inclusive community.
Interested applicants should send their curriculum vitae, a cover letter detailing research experience and how they will contribute to our goals to engender a more inclusive and diverse school, and contact information for three references to firstname.lastname@example.org.
Boston University is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. We are a VEVRAA Federal Contractor.
About Department of Biostatistics, Boston University School of Public Health
The Department of Biostatistics at Boston University School of Public Health (https://www.bu.edu/sph/about/departments/biostatistics/) is comprised of 29 faculty, who are internationally recognized for their innovation in research and scholarship in various areas of biostatistics including statistical genetics, clinical trials, surveillance, longitudinal studies, Bayesian statistics and risk prediction. Biostatistics faculty play leading roles in several large clinical trials and observational studies such as the renowned Framingham Heart Study, Long Life Family Study, and the Black Women’s Health Study. Their work has contributed new knowledge on genetic and non-genetic factors for cardiovascular disease, dementia and Alzheimer’s disease, osteoporosis and arthritis, nutritional epidemiology, healthy aging and extreme longevity. Many of these findings have been effectively translated into current clinical practice.