53 machine-learning-"https:"-"https:"-"https:"-"https:"-"UCL" PhD positions at Forschungszentrum Jülich
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Excellent knowledge and experience in programming Python Excellent knowledge and experience in machine learning Excellent ability for cooperative collaboration Very good command of written and spoken
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Master Thesis - Decoding Occupancy: Classifying User Activity from Building Power Consumption with Machine Learning At the Institute of Climate and Energy Systems Engineering (ICE-1) we focus on the
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design of hybrid electrical–optical computing architectures and (2) develop learning rules that are both technology-feasible and well-suited for machine-learning workloads. The project will consist among
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, and physics-informed machine learning open new possibilities for establishing grid foundation models. However, it is still unclear which model structures is most capable and suitable, how well they
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, machine learning applications, and analyses of individual disease trajectories. Your tasks will include: Integrate multimodal neuroimaging datasets from MRI, PET, EEG, and fNIRS studies Characterize brain
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surrogate models and experimental data from a pilot-scale settler are available. The project offers close supervision from doctoral researchers in machine learning and process control. Your Profile
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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a
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programming neural networks, machine learning theory and machine learning software frameworks (e.g., PyTorch or JAX). Curiosity-driven personality with the ability for creative and analytical thinking
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applications and algorithms that can leverage associative memories, including machine learning and LLMs, genomics, and classical data science methods (tree models, decision trees, finite automata). We
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Your Job In this position, you will join our Simulation and Data Lab for AI and Machine Learning for Remote Sensing . The lab advances interdisciplinary research and operational services by combining