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Field
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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programming applications (e.g., experimental design, machine learning for science). We do so by bringing together a diverse team of PhD candidates who will focus on three key areas: Probabilistic and
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scans and use advanced data-driven methods, including artificial intelligence (AI) and machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology
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opening for a fully funded 4-year PhD position. We are looking for highly motivated applicants for a PhD student to strengthen our research team in an interactive and collaborative environment. Learning non
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opening for a fully funded 4-year PhD position. We are looking for highly motivated applicants for a PhD student to strengthen our research team in an interactive and collaborative environment. Learning non
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degree in Computer Science, Artificial Intelligence, Data Science, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong
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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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longer sustainable. This project pioneers a new paradigm: we design smart, low-power digital AI co-processors that learn and correct the imperfections of their analog counterparts in real-time. As a PhD
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Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; a complete educational program for PhD students; multiple courses on topics such as time management, handling stress
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8 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Computer hardware Computer science » Digital systems Engineering