Post-doctoral Research Fellow in Vaccine Impact Modeling, Global Health, School of Public Health

Boston University

Post-doctoral Research Fellow in Vaccine Impact Modeling, Global Health, School of Public Health

Boston, MA
Full Time
Paid
  • Responsibilities

    Dr. Portnoy’s Research Lab in the Department of Global Health at the Boston University School of Public Health invites applications for a one-year post-doctoral fellowship, with the potential to extend for additional years.

    The Portnoy lab undertakes a range of public health research investigating the health impact, costs, and cost-effectiveness of infectious disease prevention programs in the United States and in low-resource settings, using mechanistic and statistical computer modeling. The research involves close collaboration with Vaccine Impact Modelling Consortium, a modeling consortium funded by the Bill & Melinda Gates Foundation, Wellcome Trust, and Gavi, the Vaccine Alliance.

    The successful candidate will perform economic analyses and health impact modeling to investigate the potential impact of current and future human papillomavirus (HPV) and respiratory syncytial virus (RSV) vaccines. There are also opportunities to collaborate on additional projects depending on interests and expertise.

    Required Skills

    Doctoral degree in health policy, epidemiology, health data science, biostatistics, or a related field. The ideal candidate will have demonstrated excellence in research in one or more of the fields mentioned above.

    Desired skills include:

    • Excellent analytical, organization, and problem-solving skills
    • Strong interpersonal, written, and oral communication skills
    • Experience with R (required)
    • Experience with Python and cluster computing desirable
    • Experience with Bayesian statistics and model calibration preferred.
    • Strong ability to work independently and in a team environment with collaborators, stakeholders, and research staff

    TO APPLY:

    To apply, please submit a cover letter, CV, and three letters of reference to Dr. Allison Portnoy at aportnoy@bu.edu. Please provide your materials in an email including “Post-doctoral Research Fellow Position” in the subject line.

    Informal inquiries are welcome. Questions regarding this position can be sent to Dr. Allison Portnoy at aportnoy@bu.edu

    3 References are required at minimum, 4 are allowed at maximum.

    We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

    Required Experience

  • Qualifications

    Doctoral degree in health policy, epidemiology, health data science, biostatistics, or a related field. The ideal candidate will have demonstrated excellence in research in one or more of the fields mentioned above.

    Desired skills include:

    • Excellent analytical, organization, and problem-solving skills
    • Strong interpersonal, written, and oral communication skills
    • Experience with R (required)
    • Experience with Python and cluster computing desirable
    • Experience with Bayesian statistics and model calibration preferred.
    • Strong ability to work independently and in a team environment with collaborators, stakeholders, and research staff

    TO APPLY:

    To apply, please submit a cover letter, CV, and three letters of reference to Dr. Allison Portnoy at aportnoy@bu.edu. Please provide your materials in an email including “Post-doctoral Research Fellow Position” in the subject line.

    Informal inquiries are welcome. Questions regarding this position can be sent to Dr. Allison Portnoy at aportnoy@bu.edu

    3 References are required at minimum, 4 are allowed at maximum.

    We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

  • Industry
    Education