Department / Area
Epidemiology Position Description The Department of Epidemiology at the Harvard T.H. Chan School of Public Health studies the frequency, distribution, and determinants of disease in humans, a fundamental science of public health.
In addition to pursuing ground-breaking global research initiatives, we educate and prepare future medical leaders and practitioners as part of our mission to ignite positive changes in the quality of health across the world.
Dr. Barbra Dickerman at the Harvard T.H. Chan School of Public Health invites motivated researchers to apply for a postdoctoral research fellow position in causal inference for cancer control.
The successful candidate will apply modern causal inference methods to large health databases to inform decision-making about cancer prevention, early detection, and treatment.
Multiple projects are available, including the evaluation of drugs with identified repurposing potential for cancer prevention, evaluation of dynamic screening strategies for cancer, and investigation of the optimal timing and sequencing of cancer treatments.
Rich opportunities for professional development are also available, including support for attending conferences, delivering talks, teaching, and mentoring, among other activities.
The postdoctoral fellow will be supervised by Dr. Barbra Dickerman and work closely with other team members, including faculty and researchers in the CAUSALab and Zhu Family Center for Global Cancer Prevention, as well as external collaborators.
Our team conducts cutting-edge research using large health databases to improve health decision-making. Results from our research have informed recommendations for the treatment and prevention of multiple diseases and contributed to the innovation of methods to generate valid evidence from real world data.
PLEASE NOTE : The finalist will be required to complete both the Harvard University and U.S. Veterans Administration background screening processes.
Basic Qualifications Education Requirements
A doctoral degree in epidemiology, biostatistics, computer science, or a related quantitative field
Experience Requirements
Research experience in causal inference
Technical Requirements
Strong programming skills in SAS or R
Additional Qualifications Preferred Experience and Skill Requirements
- Experience in the analysis of large health databases
- Excellent written and verbal communication skills
- Highly organized with strong attention to detail and accuracy
- An ability to work collaboratively and independently
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