2,276 computer-programmer-"Multiple"-"U.S"-"Embry-Riddle-Aeronautical-University"-"Prof" Fellowship positions
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the climate crisis while also demonstrating a strong background in communicating evidence and insights to multiple stakeholders. Please note that this post may be suitable for sponsorship under the Skilled
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, and interdisciplinary research that meets global and societal needs. Our broad mix of experience-based education programs?our signature cooperative education program, as well as student research
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data at the IBM-CC Accelerator Discovery Program (the first Quantum Computer at the Cleveland Clinic Main Campus), Genomic Medicine Institute, Miller Family Heart & Vascular Institute, Taussig Cancer
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our world class teaching hospital at the Flinders Medical Centre in South Australia to multiple rural clinical locations all the way to Darwin in the Northern Territory. Our research and teaching equip
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Research Fellow post funded through the NIHR DEMCOMM Fellowship Programme. This post supports a motivated qualitative researcher to contribute to dementia-related research, specifically focusing on the care
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, teaching and program development that will improve the health of women. Each fellow completes an individualized career development plan (ICDP) around 4 core areas essential to a successful research-based
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The Andlinger Center for Energy and the Environment invites applications for its Distinguished Postdoctoral Fellows program, with start dates as early as June 2026. This program supports outstanding
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Per Week 35 Is the job funded through the EU Research Framework Programme? European Union / Next Generation EU Reference Number 7131 Is the Job related to staff position within a Research Infrastructure
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in a qualifying post (e.g., research fellow, research assistant). About the research training As a PhD Research Fellow, you must participate in an approved educational programme for a PhD degree within
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems