493 engineering-computation-"https:"-"https:"-"https:"-"https:"-"https:"-"LGEF" PhD positions in United Kingdom
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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) programme. The post holder will work closely with Professor Ronita Bardhan and contribute to a high-impact, interdisciplinary research programme focused on advancing evidence-based urban design for population
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Discipline: Engineering & Technology, Materials Science, Mechanical Engineering Qualification: Doctor of Philosophy in Engineering (PhD) This project is a collaborative research effort between
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The rapid growth of deep learning has come at an extraordinary environmental and computational cost, yet the standard training paradigm remains remarkably unchanged. Every sample is passed through
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of Sport, Exercise, and Nutrition Education – kimberley.edwards@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: The overall theme
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, implementation, and evaluation of trials and interventions through the Adolescent Interventions for Mental Health in Bradford (AIM Bradford) programme (www.aimbradford.nhs.uk). This project is ideal for candidates
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at the Chemistry/Materials interface. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline
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to achieve, at least a 1st class honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. To apply, please contact Prof Michael Greaney
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opportunity to join the Emerging Technology and Materials research group within the School of Mathematics, Statistics and Physics. You will carry out research as part of a team of researchers working
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integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative