32 postdoctoral-composite-material-finite-element Postdoctoral positions at University of London
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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with potential applications in audio and music processing. Standard neural network training practices...
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***INTERNAL APPLICATIONS ONLY*** About the Role A position is available for a Postdoctoral Research Associate to join the laboratory of Silvia Marino in the Brain Tumour Research Centre
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About the Role Applications are invited for a Barts Charity-funded Postdoctoral Research Associate post to join the laboratory of Doctor Mathieu-Benoit Voisin within the Centre for Microvascular
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About the Role – the project and research group Queen Mary University of London has a Postdoctoral Research Assistant vacancy to join the multidisciplinary project entitled “Human Tendon-CHIP: Novel
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and Immigration website . Full-Time, Fixed-Term (18 months) Applications are invited for the post of Postdoctoral Research Associate in the Department of Mathematics for 18 months, starting 1st October
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About the Role Applications are sought for a Postdoctoral Research Assistant to undertake research investigations in collaboration with and under the supervision of Dr Özgen Deniz to realise
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of their employment with the University, in accordance with the Immigration, Asylum and Nationality Act 2006. Part-Time, Fixed-Term (12 months) Applications are invited for the part-time post of Postdoctoral Research
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-motivated postdoctoral researcher with a strong background in biology and experience in bioinformatics. Experience in multiplex proteomics and sequencing analysis and a track record of effective communication
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About the Role We are looking for a Postdoctoral Research Assistant to work with Dr Chema Martin on a Human Frontiers Science Program Research Grant project entitled “Evolutionary Biophysics
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Pregnancy. Current risk-communication materials in maternity care are often text-heavy, numerically dense, and disconnected from the lived experiences of women and families. Building on prior epidemiological