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Postdoctoral Associate Position in Statistical Methods

Research in Network and Implementation Science


Postdoctoral Associate positions in statistical methods development for network and implementation science are available in the Department of Biostatistics at the Yale School of Public Health with Drs. Laura Forastiere, Donna Spiegelman and colleagues. This position involves methodological developments and applied work aimed at the design and analysis of large-scale population-based studies on social networks to evaluate the effectiveness of behavioral health interventions in which there could be mechanisms of peer influence or spillover between units. The work will involve the development of study designs taking into account network dependence and statistical methods to identify optimal targeting strategies on networks. Applications in the prevention of HIV/AIDS and non-communicable diseases will motivate the statistical research.


Qualifications are a PhD in statistics or biostatistics, strong programming skills, as well as good written and oral communication skills. Prior course work in epidemiology, health economics and/or experience with health economic and epidemiologic data preferred. Candidates whose doctoral dissertation focused on causal inference, theoretical statistics, study design, health economics, survival data analysis and longitudinal models are encouraged to apply.

Additional Information:

Scientific questions regarding these positions can be sent to Drs. Forastiere or Spiegelman. Applications will be considered as they arrive. To apply, please submit a cover letter describing your research interests as they relate to this position, with CV and names of three references. Please be sure to indicate your qualifications in terms of each of the items mentioned above.
Please apply online.

Yale University is an Affirmative Action/Equal Opportunity Employer. Yale values diversity among its students, staff, and faculty and strongly welcomes applications from women, persons with disabilities, protected veterans, and underrepresented minorities.