672 phd-position-for-fully-funded-reserch-in-computer-vision Postdoctoral positions in Uk
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/2028. About You You will have a PhD in a relevant scientific discipline and sufficient specialist knowledge relevant to the project to be able to make a start on day one – we do not expect everyone
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The Opportunity: We are seeking a Postdoctoral Research Associate in Computational Cancer Genomics to join our team at the University of Edinburgh, funded by a Medical Research Council. This is a
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This is a theoretical/computational postdoctoral position for the prediction and development of strongly correlated materials for use in quantum technologies. Project activities include
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-year position funded by a Wellcome Neuroscience in Mental Health award. The GPS (Goal Planning in Psychosis) study is a unique cross-disciplinary, cross-species programme investigating how prefrontal
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-year position funded by a Wellcome Neuroscience in Mental Health award. The GPS (Goal Planning in Psychosis) study is a unique cross-disciplinary, cross-species programme investigating how prefrontal
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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require close cooperation with other research groups. The position requires PhD in computer science, engineering, or a related field Excellent research track record in AI and sustainability or cloud
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About the role We are seeking a highly motivated, a postdoctoral researcher in computational biology. We investigate how immune cells interact with their environment in the human gastrointestinal
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experience: Essential criteria PhD in computer science, AI or related area Proven experience of knowledge engineering and semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity