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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware
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aspects of machine learning focusing on efficiency, generalization, and sparse neural networks. Currently we are expanding our expertise by applying our theoretical findings also to robotics. Hybrid is our
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Medicine, Department of Engineering), a doctoral research project is defined and a PhD student position is open in the COMPSOIL (Computational Soil Mechanics and Foundation Engineering) research group.
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Alzheimer’s and Parkinson’s. You will work within a multidisciplinary environment alongside data scientists, software engineers, biomedical researchers, and clinicians. Your research will focus on developing AI
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Networks for MLFFs Implement and test uncertainty-aware loss functions Study calibration and post-calibration for predictive uncertainty Integrate uncertainty modules into MLFF architectures Detecting
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of improved workflows in field studies These tasks will be carried out within the Marie Skłodowska-Curie Doctoral network METAMIC 3 - Metaproteome-based leveraged microbiome management in the context of One
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of the finite element method (modelling assumptions, boundary conditions, mesh/element choices, convergence checks). Experience with at least one FE tool such as Abaqus or similar. Scientific programming skills
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private sector partnerships, sponsored Chairs and a growing network of international partner universities make the FDEF a dynamic academic hub at the heart of Europe. Your role The Department of Finance
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The SIGCOM research group, headed by Prof. Symeon CHATZINOTAS, carries out research activities in the telecommunication and networking systems, including NTNs and quantum communication
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these lines, we have recently shown that individual colour centres can be integrated into silicon carbide nanophotonic waveguides with little-to-no degradation of spin-optical coherences. These finding define