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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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epidemiology as well as a relevant PhD (public health, environmental health, environmental science or engineering, epidemiology, microbiology, or similar). The applicant should have a track record of working
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of child death) study, working closely with other project staff (clinical, project administration, investigators, PhD students, and social science staff). They will supervise other ongoing research projects
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You Applicants should have a PhD in a relevant area, and/or equivalent track record in engineering management. A commitment to high-quality student education is essential, to develop and support our
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and enabling device choice/design by predicting the patient’s response. The role is funded for 3 years in the first instance. About You The ideal candidate will have a PhD in a numerate field with
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. About You You will have a PhD in a relevant field or an equivalent qualification or experience, with extensive research expertise in AI and data science at a national and international level, including
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Grade 5, Spinal Point 31 [£42,405 per annum (pro-rata)], inclusive of London Allowance. Interviews will be held in late April or early May. About You Candidate will have a PhD relevant to mental health
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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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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