49 phd-studenship-in-computer-vision-and-machine-learning PhD positions at University of Nottingham
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motivated PhD student to join our interdisciplinary team to help address critical challenges in high-speed electrical machine design for electrified transportation and power generation. Together, we will make
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a variety of machine learning algorithms trained on these data and, most crucially, will develop and implement techniques for computing the uncertainty in the prediction. The algorithms developed in
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PhD Studentship: Electrical Machine Architectures for Next-Generation NetZero E-Mobility. the University of Nottingham This project offers an exciting opportunity to undertake cutting edge research
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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conducts cutting edge research into discovering new materials for onboard ammonia cracking applications using computational and data approaches. Vision We are seeking PhD student that is motivated by zero
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Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading academics from 5 universities, and 11
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3-year PhD studentship: Scaling-Up Functional 3D Printing of Devices and Structures Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD