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Field
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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and toolsets for engineering measurements relevant to clinical settings. The project will be supervised by experts in DIC (Hari Arora), surgery (Iain Whitaker) and wider biomaterials imaging research
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is expected to soon be able to diagnose diseases occurring outside the retina. OCT images can be aberrated by the eye itself and imperfect optical design. Ocular imaging with adaptive optics promises
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Chair of Biological Imaging 07.08.2025, Wissenschaftliches Personal We are now looking for a highly qualified and motivated researcher with an engineering or physics background (f/m/x) and a
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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Image processing Optical bench instrumentation – set up and alignment Numerical modelling Scientific software development Geochronology You should possess strong communication and academic writing skills
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engineering, microscopy, and chemical biology to investigate neuroimmune interactions and mechanisms underlying neurodegeneration, both through in vitro studies and in the context of neurological diseases. We
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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instruments (e.g. Thermo Orbitrap technology). Experience in using (AP-)MALDI technique for analysis and imaging. Experience in LC/MS for targeted or untargeted studies is an asset Ability to execute research