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Description

The Department of Biostatistics and Bioinformatics at Emory University invites applications for a post-doctoral fellowship with a negotiable starting date in 2023. The initial appointment is for one year, with renewal expected if progress is satisfactory.

The successful candidate will develop statistical methods and software for analyzing public health-related data. The areas of the focus for the position are potentially broad and include nonparametric and semiparametric methods for machine learning and causal inference and fairness machine learning. Rich data sets are available to motivate statistical methods related research in these areas including data on vaccines (COVID-19, HIV, malaria, dengue fever, influenza), sequentially randomized trials, and neuroimaging.

The postdoc will work with Dr. David Benkeser and co-investigators in the Department of Biostatistics and Bioinformatics and the Emory University School of Medicine. Opportunities to collaborate with researchers outside of Emory are also available.

JOB DESCRIPTION: Helps design and conduct research within a specified field while receiving advanced training from a designated Principal Investigator to enhance professional skills and research independence needed for pursuit of a career. The specific area of research in which the trainee is mentored is determined by the department and laboratory of the Postdoc. Designs and evaluates experiments. Develops new ideas that promote current research. Prepares and publishes scientific manuscripts under the direction of the Principal Investigator. May be responsible for operation of specific equipment. May teach techniques to others, train, and supervise research staff. Positions are temporary appointments as a research trainee. The initial appointment is for one year, renewal expected if progress is satisfactory and funds are available. Appointments cannot exceed five years. MINIMUM QUALIFICATIONS: A doctoral degree or equivalent (Ph.D., M.D., ScD., D.V.M., DDS etc) in an appropriate field. Excellent scientific writing ability and strong oral communication skills. The ability to work effectively and collegially with colleagues. Additional qualifications as specified by the Principal Investigator.

PREFERRED QUALIFICATIONS: Experience with nonparametric/semiparametric efficiency theory and causal inference; experience with advanced computing (e.g., developing R packages, high performance computing); previous publications; strong writing skills.

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