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to the activities of the Machine Learning & Data Science research group, develop rigorous mathematical proofs for convergence and asymptotic analysis of deep learning models, methods and algorithms, and collaborate
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for personal and professional development Close collaboration between Empa and EPFL, bringing together complementary expertise in energy systems, machine learning, and foundation models The opportunity to shape
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NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will involve collaboration with
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interact with a set of challenging scenarios. This project is funded by the European Space Agency (ESA) and is in collaboration with Autodiscovery. TMNT will focus on a team of highly mobile Unitree A2
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equitable energy systems. This PostDoc position is offered in collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink ). IMOS develops advanced
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an established code (for example VASP, Quantum ESPRESSO). ● Research experience performing molecular dynamics simulations. ● Experience training, fine-tuning, or validating machine-learning interatomic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
serve more than a thousand undergraduate students and hundreds of graduate students and postdoctoral fellows. Our driving research ideal is collaboration-as it has been since the founding of our
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of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
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learning (RL). 2) The Automation Group: Experts in designing and deploying custom robotic systems engineered for high-throughput sample synthesis, processing, and analytical characterization. This role is
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ferroelectric memory, photonic integrated circuits and next-generation telecommunications. You'll work at the exciting intersection of experimental materials science and materials informatics, collaborating in