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, computer simulations and machine-learning analyses. The University of Nottingham offers a wide range of employee benefits. More information can be found at: https://www.nottingham.ac.uk/hr/your-benefits/a-z
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Cybercrime and online harms Open-source intelligence and investigation Serious and organised crime. You can find out more about CENTRIC at https://centric-research.co.uk/about As part of this role, you may
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distribution networks Nuclear data Fission and fusion fuels Metallurgy, and materials performance and manufacture, for the nuclear sector For more information on any of the above areas, please email dalton
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for the role. Please note we are unable to confirm individual eligibility before shortlisting. See here for more information on Skilled Worker visa eligibility: https://www.gov.uk/skilled-worker-visa
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April 2026. Informal enquiries may be addressed to Prof. Lucia Corsini: lucia.corsini@eng.ox.ac.uk Further information can be found at http://www.eng.ox.ac.uk/jobs/home Applications are particularly
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allows the successful applicant to choose a flexible balance between advanced machine learning method development and exciting applications on molecular data, including biomedicine and drug discovery
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preferred PI and department/research group and may suggest co-mentors across the University’s rich network final lists will be provided on the call website: https://careers.univie.ac.at/en/postdoc/e-steem
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Hardware Implementation”. This project is funding by the EU funding schema CHIST-ERA and comprises a European consortium. This consortium is led by the Centre for Secure Information Technologies (CSIT: https
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conditions. About the role We are seeking a highly motivated postdoctoral Research Associate in research data science and analysis to join Professor Gerome Breen’s internationally recognised team at King’s
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for the transition from fossil carbon towards a sustainable net-zero future, as well as growth and sustainability of the UK economy and beyond. https://www.nottingham.ac.uk/news/c-loop-ukri C-Loop is a collaborative