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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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and culture within it. Who we are looking for We are looking for an enthusiastic, self-motivated candidate, with a 1st or high 2:1 degree in computer science or mechanical engineering. The candidate
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/ physics/ meteorology/ engineering/ biology. Experience in a computer programming language (e.g. Fortran, Python). A general understanding of the importance of the scientific method is essential. A previous
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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computational approaches. You will play a hands-on role in generating and analysing high-quality data that fuels discoveries, publications and therapeutic innovation. https://www.rdm.ox.ac.uk/research
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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degree in Electrical Engineering, Biomedical Engineering, Mechanical Engineering, or a related field, with a genuine interest in Wearable Technology, Sensor Development, Biomedical Devices, and Data
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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had