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Field
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algorithms, analysis pipelines, and software in order to establish and ensure effectiveness and scalability of computing infrastructure. Provides consultation for and expertise with computer applications to
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Description The Institute for Computer Science, Artificial Intelligence and Technology (INSAIT ), created in partnership with Switzerland’s ETH Zurich and EPFL, is seeking candidates for multiple faculty
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, as it involves boiling off lots of water. Innovation is required on multiple scales and there are multiple unanswered questions: Can we replace distillation by other technologies e.g., liquid-liquid
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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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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms
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and techniques. Optimizes and extends algorithms, analysis pipelines, and software in order to establish and ensure effectiveness and scalability of computing infrastructure. Provides consultation
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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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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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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