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Field
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approach is a method that is both formally rigorous and practically efficient for the verification/validation of quantum devices. Candidate’s profile Knowledge of quantum computing and an understanding
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associated numerical methods and AI, will be used with High Performance Computing (HPC) to improve understanding of key flow physics and inform future HPT design. Skills and Experience Required: Applicants
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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. The successful candidate will also have the opportunity and be expected to develop and conduct their own PhD research on how racism creates epistemic injustice and restricts formal and informal carers
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brain decoding methods and test the extent to which these generalise across brain areas and species. You will be working with an interdisciplinary team led by Prof Andrew Jackson funded by the Advanced
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will be tasked with the development of new models for the early detection of CIN cancers, applying bleeding edge computational methods and machine learning approaches to improve detection and
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, lack of transparency, safety assurance, and sustainability. You will work at the forefront of AI research, exploring formal and dynamic verification methods, explainable AI, and data space integration
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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your formal application, please name Prof Peter Munro as your proposed supervisor and include Project Code 24001. Contact: For informal inquiries please contact Prof Peter Munro who will be happy