HARVARD UNIVERSITY

Postdoctoral Research Fellow Positions in Network Science and Biomedical Smartphone Research

Location
Massachusetts, United States
Posted
03 Nov 2018
End of advertisement period
01 Dec 2018
Ref
8597
Contract Type
Permanent
Hours
Full Time

School

Harvard T.H. Chan School of Public Health

Department/Area

Biostatistics

Position Description

The Onnela Lab in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health is seeking candidates with a Ph.D. in biostatistics, applied mathematics, statistical physics, computer science, or a related quantitative field for two-year Postdoctoral Research Fellow positions. These positions involve developing statistical methods, data analytic tools, and mathematical models for analyzing two different types of systems. In the first area, statistical network science, we develop methods that are at the intersection of statistical learning and network science with applications in social and biological networks. In the second area, smartphone-based digital phenotyping, we develop tools and methods for analyzing data collected by our smartphone platform. Our ongoing applied studies in this area involve diverse patient populations from neurology to psychiatry and oncology. The candidates can focus on one of these areas only or may work across both, depending on interests and expertise.

Basic Qualifications

Doctoral degree in biostatistics, computer science, applied mathematics, statistical physics, or a related quantitative field. Excellent programming skills in Python or similar language, as well as strong oral communication and writing skills are required.

Special Instructions

For more information about the lab, please visit https://www.hsph.harvard.edu/onnela-lab/.

Contact Information

Kenzie Carlson

Contact Email

biostat_postdoc@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.

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