31 phd-position-for-fully-funded-reserch-in-computer-vision Postdoctoral positions at University of London
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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About the Role To undertake research investigations in collaboration with and under the supervision of Prof Gareth Sanger in order to realise the objectives and development of the research programme
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biomedical data scientist / computational biologist to join our highly collaborative team at QMUL. PhD (or close to completion) or research qualification/experience equivalent to PhD level in the relevant
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to their own research interests. About You Candidates should have a PhD in a relevant discipline or will have obtained it by commencement of the position. Candidates should have some experience in multi
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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help supervise associated PhD students. The successful candidates will join large, supportive research teams led by Profs Knight, Screen and Connelly all working collaboratively at Queen Mary. This is an
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About the Role Barocaloric solid-state cooling is a promising new technology that has potential to dramatically reduce the carbon cost of cooling and refrigeration. In an EPSRC-funded collaboration
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About the Role Applications are invited for an MRC-funded Postdoctoral Research Associate post to join the laboratory of Dr Tom Nightingale within the Centre for Microvascular Research. This is a
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to work on a project investigating mechanosensing in flies (Diptera). This post will focus on using detailed wing geometry models and free flight kinematic measurements in computational fluid and structural
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and