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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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group working on the LHCb experiment at the Large Hadron Collider. The successful candidate will focus on developing LHCb’s real-time data analysis systems, including the GPU -based software
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. AlphaFold-class methods), molecular modeling software such as Rosetta, and GPU-accelerated computing. You will build robust and scalable computational pipelines and drive the project scientifically and
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in hardware–software integration, GPU/FPGA acceleration, or translation of research into prototype systems would be an added advantage. Ability to work independently while contributing effectively in
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Pontificia Universidad Católica de Chile | 2 months ago
. Additionally, the IA-PUC/AIUC hosts two supercomputers and a GPU cluster, available for numerical simulations, large databases, and data analyses. In anticipation of the ANID FONDECYT call for applications
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Vision-Language-Action models and their fine-tuning, evaluation, or extension. Multimodal sensor integration (force, tactile, vision) into policy learning pipelines. GPU-parallel simulation, large
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training. Multi-scale imaging: micro-CT, SEM, FIB-SEM, or synchrotron data handling. HDF5 / Zarr data schemas and GPU-accelerated volumetric processing. Published work in generative models, synthetic
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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