Harvard University Postdoctoral Research Fellow in Cambridge, Massachusetts
Title Postdoctoral Research Fellow
School Harvard T.H. Chan School of Public Health
We are seeking a postdoc to join a new epidemiologic modeling project begun in the Department of Epidemiology at the Harvard T.H. Chan School of Public Health. The ideal candidate will have either experience or interest in simulation or agent-based modeling of infectious disease. The project aims to investigate the role of pre-exposure prophylaxis (PrEP) on reducing new infections of HIV in the United States. The postdoc will be given the opportunity to lead analyses based on the study aims as well as their own interests. Ideally, the postdoc will be interested in leading analyses on modeling methods, effectiveness of population-based PrEP strategies, network analyses, related evidence-based HIV prevention strategies, or broader epidemiologic methods and substantive HIV/STI research.
Although the desired technical skills will vary depending on the experience of the postdoc candidate, experience in simulation modeling is encouraged, as well as other potentially advantageous skills, e.g., programming in C++ or Python, basic statistical software (STATA/SAS/R), or other forms of epidemic modeling. The postdoc will have the opportunity to grow as a researcher in the rich academic environment at the Department, School, and University, which includes many HIV-related centers and institutes: The Center for AIDS Research (CFAR), Center for Biostatistics in AIDS Research (CBAR), and the Harvard AIDS Initiative. The postdoc candidate will lead their own research questions within the scope of the project, and help direct overall research progress among the wider team of RAs, a study programmer, and investigators at Harvard and collaborating institutions. The position will be located in the lab of Professor George R. Seage III, under the mentorship of the lead study investigators, Dr. Daniel Escudero and Dr. Seage.
PhD (or equivalent ScD, DSc) in epidemiology or related field (e.g., ecology, computational biology, biostatistics)
Interested candidates should contact: Dan Escudero (617) 432-1899 firstname.lastname@example.org
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 2