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position in simulation-based inference for particle physics Uppsala university Share: Facebook Twitter LinkedIn Email Application deadline October 15, 2026 Read more and apply SciLifeLab / Careers
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difference in the transition towards a sustainable future. Subject description This project focuses on the development of GPU-accelerated, high-fidelity thermal runaway simulation models for lithium-ion
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Join us in designing stable materials for sustainable energy devices with machine-learning-accelerated simulation and modeling. Work assignments The postdoctoral researcher will develop machine
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matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of collaborators and strong access to compute through national GPU systems (NAISS, e.g
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sustainability goals in the forest landscape using simulation and optimisation. The analysis will be based on spatially explicit future scenarios, developed in collaboration with various stakeholder groups
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stability, but there is still little rigorous understanding of how accuracy depends on time-step size, which varies substantially over the course of a simulation. The project's aim is twofold: to deepen the
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related subject area at MDU that exceeds one year. Applicants must be able to demonstrate knowledge and experience in: Simulation software for building and district energy systems, both commercial and
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-determinism, continuous data dependencies, testability, and maintainability. Different strategies for evaluating architectures, including but not limited to simulation, best-practice pattern evaluations
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apply them in practical engineering work. Experience in mechatronics and system integration, as well as modelling and simulation of robotic, automation, or production systems. Experience in teaching
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practical engineering work Experience in mechatronics and system integration, as well as modelling and simulation of robotic, automation, or production systems Experience in teaching within relevant technical