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Field
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numerical simulations and machine learning in order to better understand and characterize active matter systems. A possible direction is to use physics-informed machine learning techniques to connect
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and (2) develop learning rules that are both technology-feasible and well-suited for machine-learning workloads. The project will consist among others of the following tasks: Investigate and design
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The Max Planck ETH Center for Learning Systems (CLS) addresses cross-disciplinary research questions in the design and analysis of natural and man-made learning systems. The excellent engineering
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 16 days ago
catalysts. The position is available immediately, and the starting date is flexible. The doctoral researcher will work on a 3-year doctoral program and the postdoctoral position is initially for 12 months
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scales through advanced numerical modeling. Our research foci are located at both plate boundaries and within the plate interiors, inside the deep mantle and at the surface. To approach our aims, we
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FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Strong foundations in Machine Learning and Deep Learning Excellent Python programming skills Experience with PyTorch
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-style models. Pretraining may use self-supervised, contrastive, masked-modelling, or generative objectives. Own research ideas are strongly encouraged. Your responsibilities • Develop deep learning
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 8 days ago
accumulation of radiotoxic elements in the geo- and biosphere including the food chain. This also includes research on microbial activity in potential repositories for highly radioactive waste. The Group Deep
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and experience with modern deep learning frameworks (e.g. PyTorch) Solid background in machine learning, ideally with experience in NLP, large language models, or sequence modeling Interest in clinical