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SPH Post-Doctoral Fellow
IU School of Public Health | |
United States, Florida, Saint Petersburg | |
October 24, 2022 | |
The Indiana University School of Public Health-Bloomington invites applications for a post-doctoral fellow with strong data analytic and collaborative skills to join a team of researchers focused on rigor, reproducibility, and transparency and/or statistical and data analytic research in the obesity, nutrition, or aging research domains. The fellow will work with Dean David B. Allison as well as other faculty co-mentors within the School of Public Health-Bloomington. This project presents unique opportunities for gaining research experience and working on internationally impactful projects with a dynamic interdisciplinary team. The initial formal term of appointment is one year, but funds are available for longer and we expect fellows to stay at least two years with potential for renewal by mutual agreement for up to an additional one to two years. The candidate is expected to begin December 1, 2022, but may be flexible. Applications received by October 30, 2022, will receive full consideration, but applications will be accepted until the position is filled. The salary and benefits are competitive and include funding for conference-related participation and continuing education courses. During the period of the fellowship, the fellow is expected to work on campus. Indiana University is an equal employment and affirmative action employer and a provider of ADA services. All qualified applicants will receive consideration for employment based on individual qualifications. Indiana University prohibits discrimination based on age, ethnicity, color, race, religion, sex, sexual orientation, gender identity or expression, genetic information, marital status, national origin, disability status or protected veteran status. Responsibilities: Applied data analyses in obesity-related research ranging from basic science (animal studies) to clinical trials, meta-analyses, and epidemiology.
Degree: Must have a PhD. Applicants with strong data analytic skills holding a PhD from any discipline (e.g., economics, epidemiology, sociology, psychology, mathematics, engineering, etc.) will be also be given consideration.
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