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- University of Amsterdam (UvA); Published 21 Nov ’25
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Field
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(MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop
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the capabilities of fully digital Large Intelligent Surfaces. Subject description The research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent
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advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
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, high-performance computing (HPC), and computational sciences. Major Duties/Responsibilities: Participate in: (1) design and implementation of scalable DL algorithms for atomistic materials modeling
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data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms. Assist with organizing large-scale multimodal neuroimaging dataset, brain
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spanning multiple locations and entities, where complex constraints and resource interdependencies – among people, machines, and robots – demand the deployment of intelligent algorithms for orchestration
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learning on large-scale HPC systems Scalable and energy-efficient AI training algorithms Image reconstruction, segmentation, and spatiotemporal modeling High-performance computing for large-scale AI and
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on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems
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, 2022) and extended this to the triple equivalence between neural dynamics, Bayesian inference, and algorithmic computation (Commun Phys, 2025). -We validated it within in vitro neural networks (Nature
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security