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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 5 days ago
experimental and AI/machine learning skills, including deep learning, related to biometrics, such as face, fingerprint, and iris and strong communication skills, both verbal and written. Create a Job Match for
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to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position. The PhD fellow position is for a period of
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The Air Force Science & Technology Fellowship Program (AF STFP) provides nationally competitive fellowship awards for postdoctoral and senior scientists. Selected individuals have the unique
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Deadline 11 Sep 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Nov 2025 Is the job funded through the EU Research Framework Programme? Not funded
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, especially in the area of simulations. Criteria of the candidate: PhD in the field of Computational Biology, or related fields Strong publication record in leading international journals Excellent background
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must participate in an approved educational programme for a PhD degree within a period of 3 years. The deadline for applying for admission to the PhD programme at The Faculty of Science and Technology is
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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 a period of 3
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: 15081 School: Faculty of Arts and Sciences Department/Area: Weatherhead Center for International Affairs Position Description: The Weatherhead Scholars Program at the Weatherhead Center for International
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Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A
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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