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Field
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
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, testing the results against experimental data and deriving interpretative and predictive scenarios. An active contribution to the software algorithms is also wished. Teaching duties come with this position
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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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algorithms for data processing, assisted or automated flaw detection, 3D EM solvers, and synthetic aperture radar (SAR) focusing will be used to refine spatial resolution. Applicants should have, or expect
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-world error patterns: we therefore aim to go beyond the traditional depolarizing error model generally accepted in the quantum coding community. One therefore wishes to adapt existing decoding algorithms
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-body positron emission tomography (PET) with magnetic resonance imaging (MRI). In conjunction with the development of algorithms, dedicated software and hardware-based simulations will be developed
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the entire system, where many interconnected modules affect each other. In this project, you will be designing algorithms to guarantee the reliable operation of semiconductor machines, together with a highly
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LEO, MEO, and GEO constellations), and complementary on-board sensors. Research will investigate algorithms for robust multi-sensor fusion and positioning assurance. A strong emphasis will be placed
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We are looking for a strong, motivated PhD-student with an analytical, algorithmic background who is interested in pursuing a PhD-project devoted to the allocation of donor organs to patients. The goal
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position (contract-based) and one PhD fellowship in Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys). The PhD position is focused on efficient algorithms