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for this postdoctoral position to work on development and scaling of the data infrastructure and software for AI applications on supercomputing systems and AI testbed systems. The postdoc will work on multimodal data
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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requirements as applicable to in situ/operando measurements, controls, data acquisition, and metadata/interface requirements, commissioning, verification, and acceptance test criteria appropriate for an MIE
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-quality software. Strong software development skills, particularly in Python or C++, with experience in data analysis, simulation, or workflow scripting. Excellent verbal and written communication skills
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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devices, with emphasis on lithium-ion, sodium-ion, and lead-acid battery systems. Modeling and analysis will leverage tools such as COMSOL, MATLAB, Excel, Python, and related scientific software. The role
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and contributing to reusable research software when appropriate. Position Requirements Required skills, experience and qualifications: PhD in computer science, applied mathematics, electrical
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Demonstrated experience with HEP or NP detector design and simulation Proficiency in scientific software development (e.g., C/C++, Python, or similar languages) Ability to model Argonne’s core values of impact
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(HPC) environments and large-scale data management. Experience with version control (e.g., Git) and collaborative software development practices. Experience with real-time analysis and instrument control
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applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems Interest in software development, with particular emphasis on the Python