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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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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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tightly coupled to GPU-accelerated high-performance computing using Lund University’s national e-infrastructure. You will join an interdisciplinary research environment that values scientific independence
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environment with a wide network of collaborators, generous support for conference travel, and access to national HPC resources (NAISS) and local GPU infrastructure. This Postdoc position is part of the
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principles and research data management. Experience with high-performance computing, cloud computing, GPU acceleration, or distributed data processing. Experience participating in international scientific
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, incubators, shakers, and high-throughput laboratory automation.You will also have access to a dedicated Linux-based GPU computing cluster for AI-driven protein design and machine learning, enabling the