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degree in computer science or related discipline Strong interest in applied machine learning, including but not limited to deep learning Strong interest in image analysis / computer vision and pattern
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design process of cyber-physical systems. The key idea is to represent a large set of design alternatives in a concise model with a well-defined semantics and then apply efficient verification techniques
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adjustment of cubesat formations, RF synchronization, interferometry between moving platforms, calibration of RF front-ends, ground testing making use of drones, cubesat systems, on-board processing, data
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prototype development Carry out your research with collaborators at the SnT and members of the large European GLITTER consortium Disseminate your findings at conferences and in journal papers Provide
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loading, a numerical procedure is to formulated and implemented to accelerate the simulations. Your Profile Aspiring researchers interested in a PhD project with strong industrial relevance are encouraged
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the following tasks: Carrying out research on the predefined topic: testing web applications Proposing solutions Implementing prototype tools Producing results Disseminating results through scientific
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the feasibility, practicality and success evaluation of prototype implementations. The team you will be working with: Mike Papadakis Yves Le Traon PhD Student Role: Under the direction of a professor, the candidate
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candidate, you will be expected to program prototype tools showcasing the practical benefits of your research outcomes. The supervision team you will be working with is: Maxime Cordy: research scientist
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free language classes to career resources and extracurricular activities But wait, there's more! Complete picture of the perks we offer Discover our Partnership Programme How to apply Applications should
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activities But wait, there's more! Complete picture of the perks we offer Discover our Partnership Programme How to apply Applications should include: Full CV, including list of publications and name (and