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application from qualified women. About the position The position involves both teaching and engaging in innovative research projects on tractor autonomy, path-planning algorithms, soil compaction modeling, and
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learning for dementia prediction. see here: https://ai-med.de/wp-content/uploads/2025/04/PhD_Position.pdf PhD Position: Interpretable Models for Dementia Prediction Lab for Artificial Intelligence in Medical
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://github.com/FZJ-IEK3-VSA/RESKit ). This framework currently uses historical weather data to model energy output and will be further developed to allow the simulation of renewable electricity production under
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combining experiments with computational analysis. Interest developing new methods and analysis tools for emerging model systems. What we offer A cutting-edge research environment Pleasant working atmosphere
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sites will not be located directly at the source of emissions, which will require transport infrastructure. As part of this work, you will model spatially resolved transformation paths for the energy
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Max Planck Institute for Neurobiology of Behavior - caesar, Bonn | Bonn, Nordrhein Westfalen | Germany | about 1 month ago
analysis tools. Excited about combining experiments with computational analysis. Interest developing new methods and analysis tools for emerging model systems. What we offer A cutting-edge research
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The Leibniz Institute for Prevention Research and Epidemiology – BIPS in Bremen, Germany, invites applications for a three-year PhD program in epidemiology, statistics, and prevention and
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therefore teams up materialists, electrical engineers, and computer scientists of TUD, RWTH Aachen and Gesellschaft für Angewandte Mikro- und Optoelektronik mbH ( AMO ) in Aachen, Forschungszentrum Jülich
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with you on board! We are seeking a highly motivated PhD student to join our research team studying the role of NMDA receptors in psychosis, using translational mouse models of anti-NMDA receptor
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools