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position within a Research Infrastructure? No Offer Description The project aims at pushing the boundaries of machine learning and reinforcement learning with applications to healthcare data. This project
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collaborations with academia, industry, and society. The Data Science & AI division within CSE engages in research and education within a growing area encompassing Data Science, AI, Machine Learning, and its
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work with Prof. M. Ángeles Serrano and Prof. Marián Boguñá at the interface between Network Science and Machine Learning. The goal is to merge the best of the two worlds to produce a new generation of
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education within a growing area encompassing Data Science, AI, Machine Learning, and its applications. About the research This position is part of a joint collaboration between the two of the largest research
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) that can benefit either from: (i) continual learning, and (ii) spiking neural networks implemented in neuromorphic processors. Design and develop the machine learning algorithms able to provide a good
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17 Apr 2024 Job Information Organisation/Company University of Galway Research Field Computer science » Programming Researcher Profile Recognised Researcher (R2) Country Ireland Application Deadline 1 May 2024 - 17:00 (Europe/Dublin) Type of Contract Temporary Job Status Full-time Hours Per...
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, machine learning, information security, and data analysis. Further, experience with federated learning, transfer learning, GAN, and programming of distributed systems is helpful. The application must
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 17 days ago
in Machine Learning for Health (f/m/x) 102396 Full time Neuherberg near Munich Home Office Options We are Helmholtz Munich. In a rapidly changing world, we discover breakthrough solutions for better
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analysis and machine learning. Active researchers in Artificial Intelligence include Thomas Schön and David Sumpter (machine learning); Ida-Maria Sintorn and Carolina Wählby (AI and image analysis); Ginevra
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the University of Luxemburg, is to develop reliable, efficient, and accurate machine learning force fields (MLFF) for molecular dynamics simulation of systems sizes ranging from ~1000 to 100.000 atoms while