Postdoctoral Research Fellow/Research Associate, Biostatistics
Postdoctoral Research Fellow / Research Associate Position in Data Science and Smartphone-Based Digital Phenotyping
Harvard T.H. Chan School of Public Health
The Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, is seeking candidates with a Ph.D. in biostatistics, applied mathematics, statistical physics, computer science, or a related quantitative field for a two-year Postdoctoral Research Fellow or Research Associate position to work on a digital women’s health study. The researcher will work as part of a large interdisciplinary team consisting of epidemiologists, clinicians, biostatisticians, computer scientists, and biomedical engineers to develop and apply methods that integrate actively-collected longitudinal survey data together with passively collected data collected by a smartphone or wearable device. This is a very exciting research area for anyone with a serious interest in temporally dense, high-dimensional data and its applications in women’s health. Specific data types will include but are not limited to physical activity and physiologic data, sleep data, and survey-based data on disease history and lifestyle factors. Methodologic challenges within this context will include dealing with missing data and dropout, the development of multi-stage sampling strategies for validation sub-studies, as well as the potential to develop novel data integration methods that link survey and passively collected data with other data types, such as electronic medical records.
Doctoral degree in biostatistics or statistics, computer science, applied mathematics, statistical physics, or a related quantitative field. Excellent programming skills in Python is essential, and familiarity with big data analysis frameworks, such as Apache Spark, is advantageous. Must be able to work independently and in a team environment and must have strong communication skills. Appointment at the research fellow or associate will depend on prior experience of the successful candidate.
Academic questions regarding this position can be sent to JP Onnela (email@example.com)
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
Maximum Number of References Allowed
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