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and optimization of machine learning methods. Candidate’s profile An ideal candidate would typically have: a strong degree or higher qualification in a relevant field (e.g. computer science, mathematics
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at the edge. The project explores advanced topics such as TinyML, neuromorphic design, reconfigurable logic, and autonomous fault recovery, with applications ranging from aerospace, energy, and robotics
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Number of Positions: 1 Eligibility: UK Only Funding: School of Computer Science Scholarship, in support of the EPSRC Grant: Mixed precision in Krylov Methods, providing the award of full academic
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relevant to the proposed PhD project (inc. computing, mathematics, engineering etc.). Enthusiasm for research, the ability to think and work independently, excellent analytical skills and strong verbal and
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There is increasing interest internationally in the application of ‘soft engineering’ techniques that work with the natural environment and slow / temporarily store water that would otherwise impact
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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to submitting an online application, you will need to contact the project supervisor to discuss. Online applications click the 'Apply' button. Please select Computer Science on the Programme Choice page. You will
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College London, who is an expert in bone biology and will provide the high-resolution computed tomography (CT) scans of the bone. The overall goal of the project is to use computational approaches to map
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programming skills in Python/MATLAB, and an interest in digital twin technologies, cybersecurity and machine learning. Entry Requirements Acceptable first degree: Computer Science or related disciplines
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of Physics & Astronomy and Computer Science, joining an interdisciplinary team bridging spintronics, photonics, and materials science. During your PhD you will gain hands-on experience in: ultrafast laser