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for deployment on large-scale computing resources, such as high-performance computers (e.g., Perlmutter, Aurora, etc.). This includes tasks such as automating model design, optimizing hyperparameters, and training
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their environmental impacts including energy use, water use, emissions, and resource depletion. Coursework and some project experience in application of mathematical optimization, statistics, or machine
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We are seeking a highly motivated Postdoctoral Appointee with a strong background AI/ML specifically in the development and application of Large Language Models (LLMs) tailored for scientific use
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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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investigate the relationship between the physical and chemical properties of sulfur cathodes and their electrochemical performance. Experience with various electrolytes, including both liquid and solid
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, energy, and critical materials supply chains. In this role, you will be responsible for analyzing existing and future supply chains, with a specific focus on understanding the complexities and challenges
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of scientists and High-Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state
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) at Argonne National Lab (near Chicago, USA). The postdoctoral researcher will work on the development of large-scale molecular dynamics, AI and machine learning based analysis to understand ferroelectric
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valuable resources. To do so, we identify new mechanisms to drive selective electrocatalysis in complex aqueous mixtures. Experimental work involves precision atomic layer deposition synthesis and