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on algorithms, data structures, and programming languages like Python.) Working knowledge of generative AI techniques, such as GANs and VAEs is a plus. A minimum of two (2) years of full-time professional
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evaluation of cyber-physical system security solutions for distribution power grid with renewable energy sources Development of simulation models and integration of CPS security algorithms into hardware-in
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responsibilities will span all stages of research, including collecting data in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical analyses, running
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Sciences Laboratory (SISL). Responsibilities Conduct analysis, modeling, software and algorithm development in various disciplines such as underwater acoustics, ocean propagation modeling and SONAR
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design and reinforcement learning algorithms. We combine statistical methods with online reinforcement learning algorithms to provide inferential tools. The successful applicant will be expected to develop
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machine learning techniques, predictive algorithms, and AI-powered tools to extract actionable insights to drive US Commercial strategies and tactics. Manage and mentor a team of data scientists (internal
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of twelve credits per semester in support of our undergraduate and/or graduate degree programs. We are particularly interested in candidates with experience teaching courses in algorithms, artificial
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data and developing the algorithms and tools that enable the work of their team. Thus, the ideal candidate for this position must have a biological background, the ability to translate scientific
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algorithms. An understanding of when to apply what data-driven approach, from statistical techniques to generative AI models. Experience working with DOE National Laboratories (or similar R&D organizations
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advanced statistical methods to mine and analyze complex and unstructured data sets. Offers complex analysis and utilizes advanced algorithms and statistical software. Adheres to all protocols. Essential