367 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" PhD positions in United Kingdom
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from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
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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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collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI
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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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. 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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bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.04.2029 Reference no.: 5311 Your responsibilities: As a University assistant, you will contribute to the work group Machine Learning
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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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options, work-life balance initiatives and support for physical and mental health. You can find more detail on all of this and more at https://www.qub.ac.uk/directorates/HumanResources/pay-reward-and
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electron laser facilities. Contact: For informal enquiries please contact Sam Hay (Sam.Hay@manchester.ac.uk ) or Mike Hough (michael.hough@diamond.ac.uk ). https://www.manchester.ac.uk/research/sam.hay https