41 phd-position-for-fully-funded-reserch-in-computer-vision Postdoctoral positions at University of Florida
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applications for a postdoctoral research position to start in the Fall of 2026. The appointment is initially for two years, with a possible extension to a third year, subject to the availability of funds
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Classification Title: Res Ast Sctst Classification Minimum Requirements: Highest degree possible in field; Evidence of pertinent experience for the position and qualities for the academic unit. Job
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-throughput catalysis facility http://www.lsp.unina.it/lsp/. This position offers a vibrant and highly interactive academic setting along with industrial-sponsored funding, access to outstanding resources and
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such an environment through their scholarship, teaching, mentoring, and professional service. If an accommodation due to a disability is needed to apply for this position, please call 352-392-2477 or the Florida Relay
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expertise in reflectance spectroscopy and chemometrics for vegetation analysis or high-throughput phenotyping. A strong background in GeoAI, computer vision, and data fusion techniques. Experience designing
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and analysis pipeline to compute the 3 and 4 point correlation functions of Roman data. Must have PhD in astronomy or physics. This position will be initially awarded for one year, and, contingent upon
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well as collaborate with members of other CMS groups. The initial term of the position is two years with possible extensions, subject to performance, mutual satisfaction, and the availability of funds. UF is the
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on progress. Writes articles for publication. Prepares research and presents to applicable parties as needed. Compiles data for funding proposals. Trains and mentors subordinate research associates and
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Classification Title: PhD in Bioinformatics, Computational Biology, Biomedical Engineering, Data Science, or a related field. Classification Minimum Requirements: PhD in Bioinformatics
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, vegetation, and water table position on energy transmission. Co-develop and apply process-based numerical models of dune morphological change informed by collected datasets. Coordinate field campaigns