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manipulation systems for contact-rich tasks Key research challenges include: Learning reliable predictive models from sparse and noisy sensory data Incorporating semantic priors into planning and control
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of possible methodological components include self-supervised temporal representation learning for large volumes of unlabeled AE/electrochemical time-series data, switching state-space models that describe
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position within a Research Infrastructure? No Offer Description Activities The fellow will be expected to research the relationship between these technologies (big data, machine learning, and the entire
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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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combines machine learning, legal applications, and empirical evaluation in collaboration with judicial partners. The project offers a unique opportunity to work on real-world, high-stakes AI systems in
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programming and instrument control using Matlab, Python, Labview etc Machine / deep learning expertise Strong analytical skills and ability to work in a multidisciplinary team Excellent communication and
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structural mechanics, Structural Health Monitoring (SHM), Non-Destructive Testing (NDT), or related areas • Experience in data-driven methods for engineering applications (e.g., machine learning, prognostics
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Universitätsklinikum Heidelberg – UK Mannheim GmbH | Mannheim, Baden W rttemberg | Germany | about 21 hours ago
and machine learning methods applied to biological data Experience working with multiomics data integration is a plus Excellent organizatorial skills, strong commitment, motivation and ability to work
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Machine Learning Lab (AMLab) conducts research in machine learning, artificial intelligence, and its applications to large scale data domains in science and industry. This includes the development of deep
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. Additional qualifications Experience with one or more of the following areas is meriting: Bayesian statistics, mathematical modelling, probabilistic machine learning, deep learning, large language models