36 postdoctoral-image-processing-in-computer-science-"U" Postdoctoral positions at University of London in United Kingdom
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collaborate with two postdocs specialising in experimental mechanics and materials science and PhD students. About You You should have a PhD degree in Computational Mechanics or a relevant subject (e.g
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are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme. The successful candidate will work as part of a team to develop and apply deep
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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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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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About the Role Applications are invited for a full-time Postdoctoral Research Assistant to investigate mechanical sensing and mechanical memory in cardiac muscle cells and its involvement in
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and leading journals, and to undergo additional methods training. About You Educated to doctoral level in political science or a cognate discipline, you will be proficient in quantitative research
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” which examines signal processing and machine learning methods for inferring active travel activities from optical fibre signals. About You Applicants must have an Undergraduate Degree in Computer Science
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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 We are recruiting for an 18-month postdoctoral position as a part of an MRC funded project. This position will focus on investigating bacterial and host factors influencing early