The Prevention Policy Modeling Lab in the Department of Global Health and Population (GHP), Harvard T.H. Chan School of Public Health, invites applicants for a full-time, CDC-funded post-doctoral fellowship in mathematical modeling to inform policy relating to infectious diseases. We are currently seeking a postdoctoral fellow who is eager to work with us to develop and apply simulation models that capture the dynamics of infectious disease transmission within key populations. The fellowship offers a competitive salary and benefits package matched to the applicant's qualifications and experience. Collaborate with researchers in the Prevention Policy Modeling Lab and at CDC to design, develop and program transmission models of STDs, Hepatitis C and/or TB.
The Prevention Policy Modeling Lab models the health impact, costs and cost-effectiveness of infectious disease treatment and prevention programs in the United States. Our work aims to inform U.S. health policy and guide public health decision-making at national, state and local levels. We work closely with collaborators in the National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP) at the Centers for Disease Control and Prevention. Led by the Harvard T.H. Chan School of Public Health, the lab unites collaborators from Massachusetts General Hospital, Boston Medical Center, Dana Farber Cancer Institute, Yale School of Public Health, Brown University School of Public Health and Massachusetts Department of Public Health. The team includes public health scientists, physicians, epidemiologists, mathematical modelers, economists and decision analysts.
This postdoctoral fellow will work closely with Professor Joshua Salomon, the PI for this research program, and a team of faculty members and research scientists to develop computer simulation models of diseases in human populations. A range of models developed and used in this research program relate to tuberculosis, HIV, Hepatitis C, and sexually transmitted infections. The successful applicant to this fellowship will take a lead role in the development of 1 or 2 models and contribute to our wider portfolio of projects through regular participation in disease-based work groups. Model development and parameter estimation will be conducted in collaboration with partners from CDC and members of our Modeling Lab consortium. The fellow will be expected to participate as lead author in publications arising from this work and to communicate findings in oral presentations at national and international conferences. We are seeking candidates who are interested in committing to at least 2 years of work on this program (with the fellowship implemented as a one-year, renewable commitment).
Duties and Responsibilities:
Work with the Research Assistant and Program Manager to identify and acquire best available data to parameterize the model.
Optimize, test and debug model code and confirm program meets specifications.
Write and maintain documentation to describe model development, structure, logic, coding, testing, changes and corrections/updates to facilitate communication among team members.
Author and publish abstracts, poster presentations and research articles of the model and modeling results.
Participate in weekly work group meetings.
School: Harvard T.H. Chan School of Public Health
Department: Global Health and Population
The candidate must have an advanced degree (e.g. PhD) in applied mathematics, statistics, biostatistics, epidemiology, computer science, computational biology, engineering, operations research, or related disciplines. A strong background in mathematical/statistical or computational techniques and strong programming skills in C++ or similar programming language are required. An interest in infectious disease epidemiology or public health is an advantage.
Additional qualifications that are required include: Experience building models (Note: does not need to be infectious disease related)
Strong English written and oral communication skills
Ability to work independently and be proactive, flexible, conscientiousness, and responsive.
Candidates are asked to provide evidence of an already functional application that they have designed and implemented.
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, or any other characteristic protected by law.