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., PyTorch, JAX) and model development is highly desirable. Emerging Technologies: Familiarity with Agentic toolkits (e.g., LangChain, AutoGen), LLM deployment, or RAG pipelines. High Performance Computing
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capabilities. Key Responsibilities: Capturing requirements and analyzing specifications for future detector systems Performing conceptual design and system-level optimization using emerging computing
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Knowledge on numerical linear algebra, numerical methods, high performance computing, or other related fields Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time
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Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork
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machine learning models at a world-class high-performance computing facility The candidate will have access to state-of-the-art computing resources, including: NVIDIA DGX-2 Systems: Powerful platforms
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science, including electronic structure methods molecular dynamics, and scientific machine learning. Experience with High-Performance Computing (HPC) systems and intelligent workflows. Demonstrated
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interfaces. Programming and HPC: Strong scripting and data analysis skills; experience with high-performance computing environments and job schedulers. Demonstrated ability to work in multidisciplinary teams
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. Candidates should have demonstrated interest and expertise at the interface of high energy physics, dark matter phenomenology, condensed matter physics, and quantum information science. In addition to the core
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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Laboratory’s High Energy Physics (HEP) Division
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: - Comprehensive understanding of applied computational materials science, including electronic structure methods and molecular dynamics. - Experience with High-Performance Computing (HPC) systems and intelligent