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sciences, law, and philosophy. Four WPs address citizen-empowerment-scenarios (CES) in healthcare, mobility, public governance, and healthy living. Each PhD position is embedded in one work package and
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storage, but their widespread deployment is limited by challenges in energy density, stability, solubility, and cost of electroactive redox compounds. The PhD candidate will develop and apply machine
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. Methodological Approach Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong
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is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning to apply for the PhD position within
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machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it an advantage if you bring one or more
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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group? Do you enjoy creating complex machines that have never existed before? Do you want to explore physics that nobody else has seen? Maybe you want to join our team as a PhD on our journey
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from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques to uncover
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Vacancies PhD position Social dynamics of energy communities in the Dutch energy transition Key takeaways Social dynamics shape behaviours that can accelerate or hinder the Dutch energy transition
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, including abstract geospatial workflows; design AI- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute