671 fully-funded-phd-program-computer-science-eth Postdoctoral positions in United Kingdom
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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. Support if required, the development of proposals for research funding. Candidate PROFILE: PhD in Organic Chemistry, Polymer Science, Materials Science, or related subject. Expertise in electrochemistry
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This is an externally-funded PDRA position supporting the UKRI/NERC Seedcorn Funding project “Developing a framework of key predictors of antimicrobial resistance emergence and transmission in
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range of disciplines, funded by the Leverhulme Trust to increase knowledge of how the relationship between humanity and the natural world is changing, and how we might maintain and develop a sustainable
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We offer a Postdoctoral position (24-months) in Merino Lab (University of Liverpool-(ISMIB)). This position is funded by the Springboard Award, the Academy of Medical Sciences (Start-date-September
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We offer a Postdoctoral position (24-months) in Merino Lab (University of Liverpool-(ISMIB)). This position is funded by the Springboard Award, the Academy of Medical Sciences (Start-date
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the UKRI through the Frontier Guarantee Programme to Dr Jani R Bolla. The work is to be conducted in his lab in the Department Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB
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hardware-level noise suppression, quantum error mitigation, all the way to full fault-tolerant computation. This post is primarily funded by the EPSRC Quantum Technologies Fellowship held by Dr Cai
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You will have a PhD in Computer Science or a related discipline or will have obtained it by commencement of the position. Successful candidates will have experience of model training methodologies