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Field
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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microscopy and atom probe tomography will be prepared. Finally, you will merge the images by means of deep learning algorithms. Your tasks in detail Development of the experimental protocol for the imaging
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This project aims to develop outcome measures for early detection of neurodegenerative disorders using artificial intelligence (AI) and various sensing modalities, offering personalised support to
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to muon g-2 from lattice Quantum Chromodynamics and algorithmic developments for multi-level and RG-improved simulations (research group of Urs Wenger) C.) Study of multi-hadron systems, with a focus on
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ambitious new project on the safe deployment of medical imaging AI. The purpose of the role is to conduct world-leading research on AI for medical imaging. The goal is to develop methodologies and
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leverage low-precision accelerators for scientific computing by using a number of tricks, known as "mixed-precision" algorithms. Developing such algorithms is far from trivial. We can look at computational
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. Key Accountabilities • Design and develop embedded AI algorithms for appliance profiling using smart meter data • Benchmark performance against state-of-the-art NILM approaches using datasets like
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formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
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equations into AI-based models to solve fluid sensing problems in a robust and efficient manner. Your role may include developing new optimization techniques, coding new algorithms, creating new mathematical
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to material, cutting tools and parts production. The PhD project will therefore focus on the development of an integrated system combining direct and indirect tool wear monitoring for reliable residual life