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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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). 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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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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experience and lessons learned, and the gathering of feedback; Contributing to the continuous improvement of working procedures, tools, processes, expert working methods and delivery methods (lessons learned
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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
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August 2026 are welcome to apply. A deep interest in, and basic knowledge of, key topics in language evolution, language change, language learning, human evolution, and communication. Hands-on experience
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cybersecurity expertise with modern AI techniques such as machine learning, deep learning, or large language models? Then we strongly encourage you to apply. You will join an established team with 25+ members
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Resilience from Space (ERS) and ERS SoS (EO/SAR, Comms and PNT), deep-space PNT (Moonlight, Novamoon, Lightship, SSI Navigation), future demonstrators (RFI geolocation, formation-flying satellite systems), and