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Supervisors: Dr Negar Gilani and Professor Richard Hague The Centre for Additive Manufacturing (CfAM) Research Group within the Faculty of Engineering at the University of Nottingham, recognised as
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, and travel related to the project. Overview ReNU+ is a unique and ambitious programme that will train the next-generation of doctoral carbon champions who are renowned for research excellence and
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adaptation for industrial simulation. The skills developed through this work will align strongly with careers in scientific computing, engineering simulation and applied machine learning for design and
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work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. The Department of Computer Science is an
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of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology. The programme focuses on adrenal
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supervised by: Dr Joschka Roffe, School of Informatics, University of Edinburgh Dr Stergios Koutsioumpas, School of Informatics, University of Edinburgh Dr Vivek Chidambaram, National Quantum Computing Centre
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with other Doctoral Candidates and engage in secondments to technical and clinical partners within the consortium. Research Fields Applied Mathematics, Computer and Data Sciences, Biomedical and Chemical
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28 Nov 2025 Job Information Organisation/Company Queen's University Belfast Department Centre for Secure Information Technologies Research Field Computer science » Cybernetics Engineering » Computer
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This PhD “Novel use of AI in Marine Monitoring” will focus on marine monitoring in NEOM Nature Reserve (NNR) within northern Saudi Arabia. The PhD will develop techniques for automation in surveying marine biodiversity, with an overall aim of decreasing the time between surveying and meaningful...
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-grade undergraduate degree (first class or upper second) in Computer Science or MSc in related field. Skills Knowledge of programming, Computer Science, Computer Vision, Machine Learning, or related