418 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" Fellowship research jobs in United Kingdom
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to a flexible working approach. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/407130/research-fellow-in-… Requirements Additional Information Work Location(s) Number
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10 days professional development activities per year (pro-rata). Where to apply Website https://www.timeshighereducation.com/unijobs/listing/407559/research-fellow-in-… Requirements Additional
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General enquiries: Email: recruitmentservices.people@manchester.ac.uk . Technical support: https://jobseekersupport.jobtrain.co.uk/support/home 0161 850 2004 This vacancy will close for applications
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& Professional Learning team. -All FMH staff are entitled to ten days staff development per year (pro rata). Please speak to your Line Manager about how you can utilise these. Access to on-site childcare, shopping
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dynamic group investigating mitochondrial genetics and function using Drosophila as the model (http://themalab.co.uk ). The candidate will use genetic and biochemical approaches to study mitochondrial DNA
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Please apply on the University website with your CV and cover letter also answering the criteria questions. Further details Job Description Where to apply Website https://www.timeshighereducation.com
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the project forward and translate our research into tangible innovations for the UK’s growing photonics sector, building upon our recent work published in Nature (https://www.nature.com/articles/s41586-025
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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-benefits/ . Queen's University is committed
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About the Role A fantastic opportunity has arisen for a Senior Research Fellow to join the Power Electronics, Machines and Drives Research Institute (PEMC) at the University of Nottingham and become
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climate will warm and recover in a net-zero future. As part of this project, you will apply machine learning (ML) methods to discover reduced-order models from data and develop GenAI-based techniques