361 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" PhD positions in United Kingdom
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data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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can find more detail on all of this and more at https://www.qub.ac.uk/directorates/HumanResources/pay-reward-and-benefits/ Queen's University is committed to promoting equality of opportunity to all. We
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for representing and combining multimodal information over time. Grounded in machine learning, representation learning, and efficient algorithms, the work addresses real-world challenges in sustainable and
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. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect
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on the lab can be found at https://www.sysneurodevlab.org/ Eligibility & How to apply: Please submit a formal application using the online admissions portal (via the ‘Apply’ button above) attaching a CV
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Fibre reinforced composites have excellent in plane strength and stiffness and are being used in increasing quantities in aerospace, sports, automotive and wind turbine blade industries. However fibre reinforced composites are weak in their through thickness direction. This weakness can result...
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to undertake a 4-year, enhanced stipend PhD studentship, within the Digital Metal CDT https://digitalmetal-cdt.ac.uk/ at the University of Nottingham. The Centre for Excellence in Coatings & Surface Eng
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to
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an attractive annual tax-free stipend; Join a multidisciplinary cohort to benefit from peer-to-peer learning and transferable skills development. For full information about the programme, the research projects