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Postdoctoral Fellowship in Multidrug-Resistant Tuberculosis
Epidemiology
Start date: June 15, 2020
(or as soon as possible thereafter)
Location: Boston, MA
Duration: 2 years
Salary: consistent with NIH guidelines
Project Description
Applications from PhD or
other doctoral-level degree holders are invited for a
full-time project focused on improving the quality of evidence
generated from observational treatment cohorts of multidrug-resistant
(MDR) tuberculosis (TB). The position will be based in the
Department of Global Health and Social Medicine (DGHSM) at
Harvard Medical School, which conducts research to improve the
practice of medicine, the delivery of treatment, and the
development of health care policies locally and worldwide.
Researchers at DGHSM have a long history of conducting
research on tuberculosis, HIV, and other conditions. The
selected candidate will join a team of epidemiologists and
clinicians aiming to improve access to high-quality
evidence-based care for MDR-TB around the world.
The postdoctoral fellow
will work with us on two initiatives:
(1) The endTB observational study, comprised of over 2,600
patients in 17 countries, is the largest multi-country study
of patients receiving MDR-TB treatment with the newer drugs,
bedaquiline and delamanid. The postdoctoral fellow will apply
advanced epidemiologic methods (e.g., marginal structural
models, g-estimation) to longitudinal data to answer pressing
outstanding questions related to the safety and effectiveness
of different MDR-TB regimens. Under this NIH-funded
initiative, the postdoctoral fellow will also contribute to
the implementation of a prospective cohort study of patients
receiving a shortened, all-oral MDR-TB regimen in one of five
countries. (70% effort)
(2) Research Excellence to Stop TB Resistance (RESIST-TB), in
partnership with Harvard University, is leading a research
initiative to explore the challenges associated with use of
observational data and enhance its utility to guide the
development of MDR-TB treatment recommendations.
With collaborators from multiple institutions, the fellow will
support development of tools and guidance for optimizing the
confidence and evidence gleaned from observational studies of
MDR-TB. Examples include adaptation of the STROBE checklist
with a focus on quality for guideline development and guidance
for minimizing loss of confidence in observational studies
used for guidelines due to: limitations in study design or
execution, imprecision, indirectness, inconsistency, and
publication bias. (30% effort)
The successful applicant
will be expected to participate as lead author on publications
arising from this work and to communicate findings in oral
presentations at national and international conferences. We
are seeking candidates willing to commit to at least 2 years
of work on this project.
Qualifications and Skills
Doctoral degree holders (or 2020 degree candidates) in
Epidemiology, Biostatistics or related field.
Experience applying advanced epi methods, including: marginal
structural models, g-formula and simulation studies.
Advanced programming skills in a statistical package such as
SAS, Stata, or R.
Strong writing skills.
Ability to work collaboratively.
Interested in global health.
Experience in any of the following areas is desirable:
guideline development, application of GRADE methodology,
meta-analysis, pharmacoepidemiology.
Application Instructions
Email the following items in one PDF with the surname as the
first word of the PDF file: (1) cover letter stating long-term
career aims, interest in the project, and suitability for the
position, specifically referring to the criteria listed above;
(2) curriculum vitae; (3) two or three relevant publications
or manuscripts; and (4) contact information for three to five
potential references. Applications should be emailed to:
rebecca_grow@hms.harvard.edu
See this website for
information about our department:
https://ghsm.hms.harvard.edu/.
Harvard University is 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.
Applications from women and underrepresented minorities are
strongly encouraged.
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