65 big-data-and-machine-learning-phd Fellowship positions at University of Nottingham
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to explore own research interests. We are looking for a researcher with experience of data-intensive projects involving simulations or observations, good knowledge of galaxy formation physics, and the ability
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continuous systems. The experimental data will contribute to developing an initial techno-economic evaluation to test the feasibility of utilising flower waste as feedstock. The project outcome is a first step
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members and will be required to travel in the UK and internationally for data collection, co-production and dissemination activities. The candidate will have a PhD (or be nearing completion) in History
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lead on, plan, develop and conduct individual and/or collaborative research objectives, projects and proposals either as an individual or as part of a broader programme. To acquire, analyse, interpret
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contract initially for 18 months, extendable up to 3 years contingent upon successfully meeting project milestones. What you should have: • PhD (or nearing completion) or equivalent industry experience in
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must have an MSc or PhD in forensic psychology, or a related field. The project involves recruitment online using a detailed survey, and a video interview, in a small subset of the sample. Recruitment
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colleagues to develop the research design undertaking the literature review liaison with project stakeholders data collection and analysis contributing to reports and outputs research project administration
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Applications are invited to join the Manufacturing Metrology Team (MMT) and the Quantum Information & Metrology Research Theme (QI&M) at the University of Nottingham to carry out research focused
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likely extension. Salary: Research Fellow: £31,637 to £46,735 per annum (pro-rata if applicable) depending on skills and experience (minimum £35,116 with relevant PhD). Senior Research Fellow: £45,413
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and Materials to work across several industry relevant projects and for the development of future group research strategy. MAS has a large intra-disciplinary team of researchers, engineers, technicians