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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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Universiteit Amsterdam welcomes applications for a two-year Postdoctoral position in Reinforcement Learning for Stochastic Optimization. The candidate is expected to conduct high-quality research
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algorithms to shape the liveable cities of tomorrow? Job description Human-centred AI techniques, such as Reinforcement Learning from Human Feedback (RLHF), hold great potential for supporting design
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team at AMOLF, working on fundamental questions on physical self-learning systems as part of the NWO ENW‑M1 project “How do physical learning systems learn?”. The research position is intended to start
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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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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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Vacancies Scientific programmer of libraries on testing and learning in Haskell and Python Key takeaways As a scientific programmer, you will support the development of software from a technical
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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
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PhD position ‘Courage to Correct: Balancing Error Prevention and Learning in Strategic Crisis Teams’
Vacancies PhD position ‘Courage to Correct: Balancing Error Prevention and Learning in Strategic Crisis Teams’ Key takeaways In high-stakes crises, strategic teams often aim to avoid errors at all
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Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for a PostDoc who will do research on the intersection of machine learning (ML) and statistics