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institutes in Europe, Asia, and North America. More information about the Division of Heat Transfer can be found here: https://www.ht.energy.lth.se/english/ COMPEL, "COMPetence for the ELectrification
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computation, communication and storage, optimizing GPU utilization, parallelization, inter-node communication and I/O performance on parallel file systems. You will develop solutions for monitoring
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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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AI models on HPC and GPU-based systems Provide guidance on performance optimization, scaling, and efficient resource utilization Contribute to architectural and design decisions in cloud-native HPC
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employment and promotion of teachers and appointment to docent" which is available at https://www.bth.se/english/about-bth/work-at-bth/vacancies . Meriting competencies and experience In addition to
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Experience with development of atomistic- or multiscale simulation methods, e.g in a GPU architecture, and their applications to magnetic phenomena is meriting. About the employment The employment is a
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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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demonstrate examples of your independence in research. It is also appreciated if you also have some pedagogical experience. Knowledge of and skills in MPI and GPU programming, along with experience
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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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learning programming libraries such as TensorFlow, PyTorch, or JAX is a must and experience with GPU-based experimentation and cluster computing (e.g., Docker, Slurm) a plus. In addition to the above, there