256 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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unit and then pre-processed data used as the input of the deep learning algorithm. The research will employ the SafeML tool (a novel open-source safety monitoring tool) to measure the statistical
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The Open University Business and Law Schools are inviting applications to join our campus-based PhD Programme and our new PhD by Distance Learning Programme. The starting date for both programmes is
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radios is desirable, as is an interest in the security of Cyber-Physical Systems. A solid foundation in programming (C, C++ or Python) together with familiarity with operating systems and computer networks
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Acceptable first degree - Physics, Mathematics, Natural Sciences, Engineering, Computer Sciences. The standard minimum entry requirement is 2:1. Mode of study: Full-time Start date: 1st October 2026 Funding
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that equipment’s or machine components are maintained on these schedules even without a need of repair or replacement. In addition, the stoppages to execute the schedules strategies also increase the production cost
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experience. Desirable Attributes Experience working with quantitative and textual data, writing computer code, and/or using existing Digital Humanities tools. The successful candidate will be supported to fill
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Interventional Procedures. Research methodology The unified model will leverage 50,000 patient scans from the UK Biobank imaging database, using a semi-supervised learning strategy to learn the orientation
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to neurodevelopmental conditions caused by prenatal alcohol exposure, with a UK prevalence estimated at 3.2%, among the highest globally. Individuals with FASD commonly experience challenges with learning, memory
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understanding of the interactions between sweetness and flavour intensity in frozen desserts. The successful candidate will gain a multidisciplinary experience, learning aspects of sensory evaluation
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programming (e.g., Python, MATLAB). Energy system modelling expertise with experience in academic research Preferred Skills: Educational background in Electrical Engineering, Computer Science, Renewable Energy