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Generative Modelling to apply and develop cutting-edge deep generative probabilistic models including conditional diffusion and flow matching models for synthesising Magnetic Resonance Imaging (MRI) and
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of Cambridge, UK (http://www.abg.psychol.cam.ac.uk ). The position will focus on neuroimaging and neurocomputational studies of learning and brain plasticity. Our studies combine ultra-high field brain imaging
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: analytical and forensic science; asthma and allergy; biophysics and cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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at barrier surfaces. The work will combine advanced flow cytometry, immunohistochemistry, functional antimicrobial assays, confocal imaging and molecular techniques, alongside state-of-the-art imaging
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biophysics, and cutting-edge analytical technologies. Your expertise in optical microscopy, single molecule imaging, computational imaging and data analysis will help us further develop mass photometry and
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-national ERC Synergy Programme, EndoTheranostics, aiming to revolutionise Colorectal Cancer Treatment. The post-holder will work in the School of Biomedical Engineering & Imaging Sciences, King’s College
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period of 12 months in the first instance, with potential to extend. The project involves advanced theory for new ultrafast imaging experiments and is funded by Engineering and Physical Sciences Research
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. The research requires experience in high vacuum systems, laser, molecular beams and laser desorption sources, charged particle beams and optics, velocity-map imaging detection, and the associated data processing
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with