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benchmarking of large language models (LLMs). The research profile of the group is heavily machine-learning oriented and the group has access to excellent HPC infrastructure. For more information about LTG
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for scientific discovery; integration of HPC and AI and AI-enhanced numerical methods; explainable and trustworthy AI for STEM applications; and mathematically grounded approaches applied in STEM contexts, such as
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this research, the faculty member will have access to the University of Alabama’s state-of-the-art High-Performance Computing (HPC) cluster. This resource provides the computational power necessary
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; • ability to work collaboratively in a research team, provide guidance and training to nonspecialist developers, and communicate scientific results clearly. Previous experience with HPC FE software like
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The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to develop and
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a postdoctoral fellow at the University. The individual cannot have held previous positions in the professional ranks. Preferred Qualifications Experience with NGS data analysis and Linux based HPC
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-performance computing (HPC) systems. Proven track record of interdisciplinary collaboration on research projects. Strong publication record in relevant fields such as environmental science, data science, or
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, AtomGPT). Working Knowledge Of: • Workflow tools (e.g., ASE) and HPC environments. • Software development in Python, Git-based version control, and Conda packaging. • Data integration and surrogate modeling
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information about the network: https://euraxess.ec.europa.eu/jobs/401249 1. Context and Challenges Title: Physics-Informed Neural Operators (PINO) for Ultra-Fast Tomography: Toward Fundamental and Generalizable
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skills in Python and/or R; experience with Linux/HPC environments is an advantage Experience with genomic data analysis, high-performance computing, GPU programming, or software development is a plus