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. Characterization and data analysis. Communication and dissemination activities. Support activities regarding management, coordination and exploitation. Where to apply Website https://sede.uvigo.gal/public/catalog
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in the presence of imperfections introduced by the laser and/or intensity and phase modulators. Perform a finite-key analysis of the security of these. systems in the presence of such imperfections
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, i.e., high-fidelity virtual representations of agricultural ecosystems. These digital twins will enhance our understanding of ecosystem functioning, more specifically water and carbon fluxes, supporting
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management Background: materials science, mechanical engineering, or a closely related discipline Apply: https://mgician.eu/research/doctoral-candidate-projects/dc6/ DC7: High-Performance Magnesium-Based
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. You design and perform ex-situ and in-situ characterization protocols to understand the materials activity-structural relationships. You perform extensive OER and HER evaluation measurements
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of geometric and electronic dopant environment. We will exploit access to High Performance Computing centers to accelerate our computational efforts. The project’s outcomes will serve as a guide for designing
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | about 21 hours ago
the law of the processing performed on the grounds of consent given before withdrawal thereof. Providing personal information is voluntary. More information on the protection of personal data: https
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) Expertise in further programming languages (in particular C++), GPU programming, parallel programming or high-performance computing are highly valued Keen interest in neuroscience is essential Experience with
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facilities at ICRISAT, India Performe scenario simulations, including pre- and postprocessing Participation in conferences in Germany and abroad (incl. presenting your research results) Exchange with internal
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the Sustainable Materials Innovation Hub (https://smihub.ac.uk ) at the University of Manchester, the project will deepen our understanding of the link between recycled feedstock and performance, developing