173 evolution "https:" "https:" "https:" "https:" "U.S" "U.S" Postdoctoral positions in United States
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position in MR Physics. This successful applicant will help with development of MR imaging methods to study tumor metabolism and response to therapy. The research in the MRRF is focused on the development
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our
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, atmospheric signals), data fusion across sensing modalities, and development of scalable machine learning pipelines. Work will be entirely computational and based in Seattle, with no field deployment
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(https://www.olcf.ornl.gov/frontier ) and plant phenotyping (https://www.ornl.gov/appl ). GPTgp is a pilot project initiated in September 2025 with funding from the US Department of Energy and will
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independently and the initiative to follow new ideas. Motivation to pursue career development opportunities (e.g. applying for Fellowships and Awards, promoting your research, networking, etc.). Strong verbal and
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Organization U.S. Department of Energy (DOE) Reference Code DOE-FES-2026 How to Apply Completed applications are due to be to submitted in Zintellect on January 15, 2026. Applications are reviewed
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professional references will be requested during the application review stage. The selected candidate will be required to submit official transcripts (and, as applicable, U.S. degree equivalency evaluations
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) Apply link: https://aprecruit.ucmerced.edu/JPF02033 Help contact: soe-adminopservices@ucmerced.edu About UC Merced As a condition of employment, the finalist will be required to disclose if
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complete, sign, and upload the required Authorization of Information Release to your application. Reference requirements 3-5 required (contact information only) Apply link: https://aprecruit.ucmerced.edu
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites