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computationally efficient approaches to progressive damage modelling. It is natural for you to think in terms of hybrid modelling strategies that combine physics-based simulations with machine learning when
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and different industrial outreach activities The candidate has at least the following qualifications - Applicants should hold a PhD in Computer Engineering, Computer Science, or similar - Cyber-physical
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chemical environments and correlated disorder to thermodynamic stability and transport. The research will form a central part of CENSEMAT's simulation-guided materials programme and will be carried out in
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for the Evolutionary Understanding of Human Diseases (Apollo). Information on the department can be found at https://globe.ku.dk . Our research The APOLLO Ancient Genomics Initiative is a pioneering research program led
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Take the next step in your research career
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benchmark the developed framework using project data, high-fidelity simulations including hardware in the loop, and relevant industrial case studies, assessing its robustness and computational performance
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In this position, you will be part of the research environment within the Solid and Computational Mechanics research group at the Department of Materials and Production in Aalborg. The group works with
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The SDU Adaptive Intelligence Lab (ADIN Lab) (https://adinlab.github.io/ ) located under the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA
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the Niels Bohr Institute. It functions as a primary center for fundamental research including theoretical and computational astrophysics, particle astrophysics, gravitational physics, high energy particle
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nitrogen dynamics, and climate change mitigation potentials in agroecosystems. You will be contributing specifically to the area of regional simulation using process-based models and advanced statistical