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. Applicants at the PDRA level must have a PhD in Computer Science or a related field. Expertise in intelligent decision-making under uncertainty is essential, relevant areas include influence diagrams, causal
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have a PhD in bone/skeletal research and/or immunology. Additionally, experience of in vitro (bone) cell differentiation and associated molecular, proteomic and imaging techniques is required. Experience
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at the PDRA level must have a PhD in Computer Science or a related field. Candidates must have substantial knowledge in Deep/Machine Learning, Large Language Models (LLMs) Natural Language Processing and
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Science/Electronic Engineering (or equivalent). Applicants at the PDRA level must have a PhD in Computer Science or related field. Candidates must have substantial knowledge in Deep/Machine Learning, Audio and/or
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are interested in Hamiltonian Monte Carlo and covariance-informed MCMC samplers. The project is a collaboration with Prof. Ziheng Yang (UCL) and Prof. Philip C. J. Donoghue (Bristol University). About You A PhD in
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Time Closing Date: 23.59 hours BST on Monday 15 April 2024 Interview Date: Wednesday 15 May 2024 Reference: CBS-0074-24 Post-doctoral Research Assistant We are looking for an enthusiastic PhD level
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components. About You Applicants should hold a PhD degree in Mechanical Engineering, Metallurgy and Materials, or a relevant subject (e.g. Materials Science, Engineering Mechanics, Applied Mathematics
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function. This will be achieved using validated in vitro models of human disease. The successful applicant will have a PhD in bone/skeletal research and/or immunology. Additionally, experience of in vitro
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have a PhD in a numerate field with expertise in machine and deep learning methods, supported by high quality publications. Experience of applying such methods to healthcare data is an advantage
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for the position should have a PhD (or be close to completion) in molecular and/or evolutionary biology, with significant experience in epigenetics general molecular biology techniques and/or bioinformatics. A track