Title Postdoctoral Research Fellow Positions in (i) Network Science and
(ii) Biomedical Smartphone Research
School Harvard T.H. Chan School of Public Health
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.
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.
For more information about the lab, please visit
https: // www. hsph.harvard.edu/onnela-lab/.
Contact Email 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 2
Maximum Number of References Allowed 5
Required fields are indicated with an asterisk ().