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that prioritise student learning in the age of AI. Job requirements You hold a PhD in Educational Science, Learning Sciences, Social and Behavioural Sciences, Engineering Education, Human-Computer Interaction or a
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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machine learning for molecular and material design; quantum computing for bioinformatics; quantum approaches for safe and sustainable molecular design; and benchmarking quantum simulations of materials
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. What you bring We are looking for candidates with: A PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or a closely related field; A strong publication record in
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the ambition to grow. For more information about LIACS, visit our website. What you bring We are looking for candidates with: A PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision
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energised — not deterred — by problems that sit between physics, learning and the messy real world. Your experience and profile: a PhD (completed or near completion) in Machine Learning, Computer Vision
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy to consider candidates in one of the two fields who can demonstrate a strong basis for working in this cross
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are excited by fundamental mathematical questions motivated by real-world scientific and technological challenges. You have: A PhD in Mathematics or a closely related field. A strong research background in one