32 digital-image-processing-phd-scholarship Postdoctoral positions at University of London
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
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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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. Applicants should have a PhD in Cultural Geography, Environmental Arts or a closely related field; knowledge of current climate- and ocean-related scholarship in the Blue Humanities; a track record of
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on autofluorescence (AF) imaging and Raman spectroscopy for detection of metastatic lymph nodes during breast cancer surgery. Engaging with and reporting to Dr Alexey A. Koloydenko (Department of
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physiologically relevant models will provide crucial platforms to mimic disease pathology, and better understand and treat tendinopathy. The project will generate tendon-chips using in-house commercially available
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infection experimental assays and the role will provide opportunities for career growth About You Applicants should have a PhD in a relevant field (or be close to completion) and be able to work independently
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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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project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
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-luminosity LHC. You will provide support to our PhD students and contribute to the broader activities of the group and the school. About You You will have completed or be about to complete a PhD or research
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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