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the allocation of resources for various projects, ensuring optimal utilization of personnel and tools. Mentor team members in project management best practices, providing guidance on career development and skill
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well as the needs of private organizations and institutions. Our current focus is on production and processing optimization to production capabilities for medical and industrial radioisotopes, including Ra-226, Ac
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. Proficiency in bioinformatic pipeline development and optimization. Experience analyzing and interpreting multi-omics datasets. Strong background in statistical analysis and data integration. Experience with
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other advanced AM modalities. Integrate powder R&D efforts with MDF pilot-scale AM capabilities, including powder reuse studies, flowability optimization, and material qualification. Collaborate with
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regulatory standards, developing and optimizing analytical methods for trace element and isotope ratio analysis, and maintaining ICP-MS instruments for peak performance. The successful candidate will interpret
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that integrate analog/digital architectures with neuroscience-inspired algorithms Implement and optimize biologically plausible learning rules on FPGA and high-performance computing (HPC) platforms Basic
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and optimize molten salt thermophysical property measurements, develop and utilize theoretical models and frameworks to predict salt properties, molten salt thermophysical property database expansion
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on optimization, CI/CD pipelines, and model performance monitoring (e.g., LLM/GPT frameworks). Collaborate with business and scientific teams to identify needs, gather actionable requirements, and translate them
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engineering or equivalent field and 0-2 years of research experience. Background in quantitative analysis, mathematical modeling, data science and simulation techniques with expertise in optimization techniques
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journals and conferences. This role provides a unique opportunity to work with the world’s first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric