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Dr. Debashree Ray is seeking to hire a full-time postdoctoral fellow in statistical genetics (can start as early as April 2024) for a National Institutes of Health (NIH)-funded research program. The fellow will be expected to work as part of a team to achieve common goals. Details on Dr. Ray’s most recent research in statistical genetics and genetic epidemiology are here (https://sites.google.com/view/debashree/). The fellow will be supervised by Dr. Ray, and have the opportunity to work with Dr. Ray’s long-time statistical collaborators, such as Dr. Nilanjan Chatterjee and Dr. Ingo Ruczinski, as well as with her epidemiological data collaborators.

The postdoctoral fellow will work on development of statistical methods and open-source software/tools in human genetics, with a focus on family-based study designs. Particular methodological challenges that the fellow will get to work on are non-additive genetic effects (e.g., gene-gene interaction, gene-environment interaction, parent-of-origin effect) and effects of uncommon genetic variants. The fellow will also be expected to contribute substantially to application areas (related to above research problems) using rich datasets on child health outcomes available from families with diverse ancestry.

The fellow will receive one-on-one mentorship from Dr. Ray to help achieve their short- and long-term career goals. The fellow is expected to write multiple peer-reviewed manuscripts as first author; and will be encouraged to present their work in national conferences, and gain teaching/mentoring skills through regular journal clubs and team meetings.

This is a 2-year training position in the Department of Epidemiology (Johns Hopkins Bloomberg School of Public Health), with possibility of extension subject to satisfactory performance. The fellow will get opportunities to regularly interact and possibly collaborate with other members within the Department of Epidemiology as well as the Department of Biostatistics. There will be opportunities to interact with other trainees and faculty through the Statistical Genetics working group and the lab meetings.

Candidates with Ph.D. (or soon-to-be Ph.D.) or equivalent degree in statistics, biostatistics, epidemiology, computational biology, bioinformatics, or a closely related quantitative data-intensive field are encouraged to apply. Preference will be given to candidates who can join sooner than later.

*Successful candidates will have:*
 strong research interest in statistical genetics and genetic epidemiology,
 demonstrated ability to lead statistical methodology research,
 demonstrated ability to write scientific research papers with substantive applications (publication record in peer-reviewed journals is advantageous),
 demonstrated computational skills and ability to code in one or more scientific programming languages (e.g., R, Python, C/C++),
 demonstrated ability to conduct efficient and reproducible data analyses,
 ability to work proficiently within deadlines in a collaborative environment, and
 strong communication & writing skills.

Women and members of minority groups are encouraged to apply.