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Field
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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We’re seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon
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- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute to a corpus of geo-analytical scenarios with
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University Medical Center Utrecht (UMC Utrecht); Published 31 Oct ’25 | Netherlands | about 1 month ago
by the Fondation Paralysie Cérébrale—you will help develop a machine learning-based multimodal prediction tool for CP diagnosis and long-term outcomes. This tool will integrate advanced clinical
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machine learning solutions to optimize the component lifecycle directly contributing to a more circular economy. Information In the manufacturing landscape, determining whether a component should be
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individualized diagnosis and prognosis. As part of the ENSEMBLE Project—a multinational study funded by the Fondation Paralysie Cérébrale—you will help develop a machine learning-based multimodal prediction tool
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Are you highly motivated to do PhD research in mathematical machine learning, with special emphasis on mathematical foundations for explainable AI? If yes, the Korteweg-de Vries Institute
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to: Development of computer models of the musculoskeletal system incorporating neural control pathways Train NMS model control policies via RL Your seconday tasks will include: Using learned NMS model control
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develop models that can read, extract and acquire knowledge from legacy data, coming both in the form of text and in the form of structured data (e.g. physical measurements) to predict characteristics
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stimulating, interdisciplinary environment. develop and validate machine learning models to extract digital biomarkers for atypical parkinsonism from real-world wearable sensor data. interpret findings in close