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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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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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for biomolecular systems, including prediction of protein-ligand, protein-protein, and antibody-antigen structures and affinities, and protein conformational ensembles. Design active learning algorithms and
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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
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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
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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Chirayath, ACES specializes in remote sensing and Earth science technology innovation. The Software Engineer will assist in designing and refining algorithms like Active Fluid Lensing and MiDAR. This role
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that may empower consumers to resist persuasion and reduce harmful consequences? Are you passionate about advertising, algorithms and social media? Then apply for this PhD project focused on demystifying
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work environment. We are seeking a part-time Research Assistant in computer vision and machine learning for human behavior analysis and modeling. The successful candidate will investigate new algorithms