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Field
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research in various areas of mobile network systems, multimedia and AR/VR/XR systems, robotics and machine learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts
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research position under the supervision of Dr. Chris Smith Home | Chris Smith . The lab— in the Evolution, Ecology, and Behavior section—investigates machine learning approaches for spatial population
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 14 hours ago
Position Information General Information Position Number POST40 Working Title Postdoctoral Fellow - ECE Y. Zhang Division Academic Affairs Department College of Engineering (Col) Work Unit
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project “Actively learning experimental de-signs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The PhD fellow will be part of a growing
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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, or comparable research experience, along with significant experience in machine learning, computer programming, computational biological applications. A strong background in statistics and biology. Experience
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, robotics and machine learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts. This position is part of the DRIVE project, funded by the Research Council of Norway
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factories and warehouses with autonomous components. It addresses a fundamental challenge in industrial digitalization: the lack of formal, machine-interpretable representations that integrate structural
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the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
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or game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of applicants