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analysis, has good software skills (Python, C++, ROOT) and has (some) research experience in experimental particle physics. Experience with machine learning algorithms and software is desirable but not
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repaired, reused, or discarded requires sophisticated condition assessment and decision-making capabilities. This PhD project tackles a critical challenge: how to develop robust machine learning models
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approaches. What we ask of you Required PhD in machine learning, physics, or a related field. Established expertise in deep learning (familiarity with graph neural networks, transformers, diffusion and flow
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eager to apply and valorize scientific results in this field in high-tech domains such as semiconductor machines and robots, together with highly innovative companies? Would you like to work in a team of
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will include boosted final states. The analysis strategy is strongly focused on advanced machine learning techniques, developing attention-based transformer models that will directly classify events from
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Vacancies PhD Opening: Reinforcement learning in human neuromusculoskeletal models for the control of human-inspired musculoskeletal robots. Key takeaways We’re seeking for motivated candidates
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. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine learning models without moving sensitive or large
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and programming (MATLAB, Python, R, or other scientific coding/programming). Affinity with computational neuroscience, connectomics and/or Machine Learning is appreciated. Our goal perform connectome
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computational neuroscience, connectomics and/or Machine Learning is appreciated. Our goal perform connectome analysis on neuroimaging data\integrate connectome findings across multiple speices work on developing
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and assembly of concrete PCMs. RecyWax+ offers a PhD position for molecular-dynamics simulations of novel PCM systems for thermal storage. Recywax+ is supported within the Dutch Research Council NWO OTP