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theoretical advances into practical insight and tools that can support analysis, design and decision-making for AI-enabled space systems, thereby bridging the emerging scientific theory of deep learning with
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master levels and advancing research about the integration of cutting-edge AI and machine learning as tools to enhance the analysis, interpretation, and scalability of Remote Sensing data. The successful
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modeling, molecular interactions/energetics, and tools such as AlphaFold, Rosetta, or MD simulations. Solid programming skills (Python); familiarity with machine learning is a plus. For both profiles, we
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environments, spectral sensing in the visible and near-infrared (NIR) range to estimate sugar and starch content, chlorophyll levels, and plant water status, AI-based computer vision systems to monitor crop
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, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process
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economy. As a postdoctoral researcher, you will unravel how silicon suppresses liquid copper infiltration at the atomic scale, using density functional theory-accurate machine-learned potentials and
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generation to build tools that will shape the future of home-based rehabilitation monitoring. You bring: A PhD in Biomechanical Engineering, Biomedical Engineering, Computer Vision, Robotics, or a related
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eager to combine computer vision, biomechanics, and synthetic data generation to build tools that will shape the future of home-based rehabilitation monitoring. You bring: A PhD in Biomechanical
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VITAL: Virtual Twins as Tools for Personalized Clinical Care, a European Union-funded Horizon Europe project. VITAL develops clinically relevant virtual human twin technology for personalized
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry