Harvard University Postdoctoral Fellow in Nutrition Epidemiology Methods and Population Health Disparities in Cambridge, Massachusetts
Title Postdoctoral Fellow in Nutrition Epidemiology Methods and Population Health Disparities
School Harvard T.H. Chan School of Public Health
The Department of Biostatistics at Harvard TH Chan School of Public Health invites applications for a Postdoctoral Research Fellowship focused on the development of statistical methods for longitudinal multivariate exposures for understudied populations. The postdoctoral fellow will work with Dr. Briana Stephenson and collaborate with a multidisciplinary research team to develop innovative statistical and machine learning methods to address population health disparities in nutrition and cardiovascular disease epidemiology. Areas of interest include: statistical methods for high-dimensional exposures in historically underrepresented populations, model-based clustering techniques for heterogeneous populations, longitudinal data analysis, and supervised clustering methods. Research applications will utilize data from large prospective cohort studies (e.g. Nurses Heath Studies and Black Women. The postdoctoral fellow will develop their research and training agendas through formal mentorship, seminars, conferences, and an Individual Development Plan ( IDP ) to explore and identify the fellow’s professional needs and career objectives. Flexible 2024 start date.
• Doctoral degree in Biostatistics, Applied Statistics, Computer Science, data science or related field
• Experience developing and implementing statistical methods
• Experience analyzing healthcare or population cohort study data
• Strong statistical programming skills (e.g. R, MATLAB , Python, C++, etc.)
• Strong oral and written communication skills
• Experience implementing Bayesian models
• Experience processing and analyzing large datasets
• Cover letter
• Curriculum vitae
• One-page research statement and/or one representative first author publication
• Two references
For general questions and application help, reach out to firstname.lastname@example.org .
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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