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backbone of tomorrow's Power-to-X plants. This 3-year PhD position offers a unique opportunity to build a research career at the intersection of digital twins, multi-timescale optimization, and integrated
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Take the next step in your research career at the intersection of digital twins, multi-timescale system optimization, and integrated Power-to-X systems with special focus on the electrical
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 24 hours ago
related field. This early career hire will focus on foundational statistical and optimization methods for safe and reliable AI, with applications in biomedicine and public health. Areas of interest include
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systems, from sustainable energy grids to autonomous mobility. In this ERC-funded PhD project, you develop cutting-edge game-theoretic control and optimization methods. Job description Modern society
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at the Wisedchaisri Lab investigates the structure and mechanism of voltage-gated ion channels, their interactions with drugs and neurotoxins, and the structural basis of human channelopathies caused by disease
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across traditional departmental boundaries to optimize resources, streamline operations, and maintain the operational excellence essential to student success. Job Description The successful candidate will
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The successful candidate will work with Asst. Prof. Shen Shuting on combinatorial inference under a project on "Post-learning inference for near-optimal discrete structures". The main
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-timescale optimization, and integrated Power-to-X systems. You will drive the development of system-level digital-twin and optimization methodologies, integrating electrolyzer models with renewable generation
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, and commercialization through AI-enabled approaches. The successful candidate will develop, implement, and apply computational, machine learning, cheminformatics, structural modeling, and data science
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors