682 phd-studenship-in-computer-vision-and-machine-learning PhD positions in United Kingdom
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candidate will have strong analytical skills and substantial experience in machine learning at scale. The Prorok Lab in the Dept. of Computer Science & Technology, has a variety of robotic platforms (aerial
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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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into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly motivated PhD student to join our interdisciplinary team to help address critical
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shift in the world of hardware design. On the one hand, the increasing complexity of deep-learning models demands computers faster and more powerful than ever before. On the other hand, the numerical
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax
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We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This
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the programme code: 8080F Research area: Statistics Select ‘PhD Mathematics (Full Time)' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: A
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Application deadline: 15/08/2025 Research theme: Computer Science No. of positions: 1 Eligible for: UK This 4-year PhD project will be funded by DLA studentship and is open to UK students
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end