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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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. Through outstanding patient care, groundbreaking research, and exceptional education, we are advancing the future of behavioral health and developmental science. In this role, you will collaborate with
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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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adaptive-control tools, while working closely with experimental and domain collaborators as needed. Candidates with strong computational backgrounds who are interested in learning new sensing or application
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provable guarantees AI-based cybersecurity: applying learning and AI-assisted techniques to network security, e.g., automata learning from security logs, validation of protocol models, and verified defensive
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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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for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure including LUMI
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of a collaborative team, led by Dr Sarah Morgan at the School of Biomedical Engineering and Imaging Sciences. The School is a world leading centre of expertise in AI for healthcare, providing