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. Empa is a research institution of the ETH Domain. Your tasks Amorphous materials play a key role in sustainable catalysis and energy conversion, but their disordered atomic structure makes them difficult
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. Empa is a research institution of the ETH Domain. We offer an opportunity to join an exciting project at our Structural Engineering Laboratory , within the Advanced Structural Materials and Systems (ASMS
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multifractal analysis, urban and energy planning, geography, and artificial intelligence to develop coherent and resilient approaches for urban energy infrastructures under land-use constraints such as No Net
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Research (NCCR) dedicated to advancing muon science across particle physics, quantum materials, and applications ranging from energy research to cultural heritage. Muoniverse brings together 30 research
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of measurement systems, signal processing and analysis and the assessment of measurement accuracy, robustness and long-term stability. The resulting data form the basis for model-based approaches to evaluating
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, geography, and artificial intelligence to develop coherent and resilient approaches for urban energy infrastructures under land-use constraints such as No Net Land Take. The consortium comprises four
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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Muoniverse, a Swiss National Centre of Competence in Research (NCCR) dedicated to advancing muon science across particle physics, quantum materials, and applications ranging from energy research to cultural
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are to develop highly efficient piezoelectric thin films, but also to leverage large data sets to improve our fundamental understanding of the synthesis-structure-property relationships in these polar nitride
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keen interest for bio-imaging. Completed Master`s degree in molecular/structural biology or biophysics. An outstanding academic record. Previous experience in protein imaging using atomic force