632 assistant-professor-computer-"https:" "https:" "https:" "https:" "EURAXESS" PhD positions in United Kingdom
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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We are looking for an outstanding PhD student with either strong background in computational modelling or significant experience of laboratory work, who is keen to work at the interface between
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qualification. Background knowledge and experience in engineering and computer science disciplines and in areas such as CFD post-processing (OpenFOAM), wind turbine renewable energy systems, big data management
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Centres Research area and project description: Artificial intelligence (AI)-based technologies are being adopted across various sectors at an unprecedented scale. However, the computing resources required
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, Computer Science, and Business. Academic Criteria: Bachelor's (Honours) degree in Law (or a cognate subject) at 2.1 or above (or overseas equivalent), or professional experience/qualifications; and Master's degree
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second (2.1) class degree in Physics plus a Master's degree in Physics before the programme starts. The rapid move to wireless devices and the proliferation of cloud-based technologies call for denser
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to cover living costs; Join a multidisciplinary cohort to benefit from peer-to-peer learning and transferable skills development. Learn more about the programme, available projects, and the application
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Social Statistics Sociology Academic requirements You must meet the minimum academic requirements for your preferred programme Nationality restrictions This funding is available to all nationalities
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Funding provider: Sony CSL - Paris Project start date:Flexible before October 2026 Supervisors (*lead): Aligned programme of study: PhD in Network Science About the Complex Connections Lab
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unique opportunity to work on advanced image analysis and image-driven modelling as part of a wider multi-disciplinary programme that includes mathematical modelling, cancer metabolomics and novel