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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements
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Technology » Computer technology Technology » Communication technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 4 Oct 2026 - 23:59 (Europe/Oslo) Country
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
and advance statistical, image analysis, and machine learning approaches Develop interpretable models that reveal biologically testable relationships and generate new scientific hypotheses Independently
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, or roundabout navigation will be considered. In this work, we also aim to explore the use of machine learning approaches [1][2] to personalize the driving system according to individual driver preferences
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position - Active Matter and Machine Learning In the Institute for Advanced Simulation - Theoretical Physics of Living Matter
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are seeking a candidate holding a Master 2 degree in computational biophysics, structural bioinformatics, or a related field. Knowledge of statistical mechanics and/or machine learning would be an asset
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machine-learning calibration to validation against experimental data. This job offer is part of the Horizon Europe project AIM. AIM (AI-Multiscale Integration for Waste-to-Value Digital Twins) is a four
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following areas: Robotics and Autonomous Systems Artificial Intelligence and Machine Learning Wireless Communication Systems Ultra-Wideband (UWB) Technologies Industrial Automation and Industry 5.0 Industrial
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Norwegian University of Life Sciences (NMBU), within the Faculty of Science and Technology(REALTEK), invites applications for a PhD position in Applied Causal Machine Learning. The position is affiliated with
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their research at the state-of-the-art facilities of the KIOS Center of Excellence in one or more of the following thematic areas: Control systems, computational intelligence and machine learning, autonomous