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: Statistical signal/image processing, deep learning, machine learning, neuromorphic computing Good communication skills and an appropriate publication record are essential. Solid knowledge of Python and C++ is
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. The Opportunity: We specialize in integrating multi-disciplinary approaches, combining the latest in genetics, cell biology, and biochemistry to unravel the mechanistic underpinnings of neuronal processes
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program. Through this work, you will build scientific independence, develop new science and leadership skills, and establish a growing reputation externally. Your role will be to lead a research project
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, advanced imaging techniques and numerical modelling. About the role A successful candidate will be working on the EPSRC funded project New perspectives in photocatalysis and near-surface chemistry: catalysis
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at the Photonics & Nanotechnology group, Physics Department, King’s College London, funded by the EPSRC Programme Grant New perspectives in photocatalysis and near-surface chemistry: catalysis meets plasmonics —a
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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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programmes: Chemistry; Physics; Electrical, Electronic & Computer Engineering; Chemical Engineering; Mechanical Engineering and Brewing & Distilling. In the 2019 National Student Survey Heriot-Watt University
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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of Biomedical Engineering and Imaging Sciences is a cutting-edge research and teaching School dedicated to development, translation and clinical application within medical imaging and computational modelling
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated