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Description Are you curious how Deep Learning and Online Learning can be effectively combined to create new learning paradigms? Job description Online learning algorithms achieve robustness often at the expense
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and geometric deep learning, or simulation-based inference. We welcome your unique perspective and are eager to learn how your track record, educational vision, and future research goals align with
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Engineering, Medical Image Analysis, Applied Mathematics or a related field Experience with deep learning for image analysis, preferably in medical imaging Experience with generative modelling, ideally
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Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep learning, with experience in time series forecasting or related
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You hold a PhD in Computer Science, Artificial Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep
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the measurement instrument in close collaboration with our industrial partner, Veridis Technologies. An ideal candidate has experience in vibrational spectroscopy and spectral processing. Expertise in deep learning
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). Completed academic courses in AI or machine learning. We consider it an advantage if you bring experience with Reinforcement Learning, Deep Learning and/or Explainable AI, demonstrated for example through
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Reinforcement Learning, Deep Learning and/or Explainable AI, demonstrated for example through coursework or research projects. Our offer a position for 18 months, with an extension to a total of four years upon
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programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. In particular, you will be part of the Causality team under the supervision
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across both surface and subsurface layers. This includes constructing robust feature extraction pipelines, attention-based fusion architectures, and deep learning models that accurately characterize cracks