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for Microelectronics” —a physics-informed AI framework that links composition, structure, and operating conditions to defect evolution and functional performance. The successful candidates will lead experimental
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is beneficial Experience with chemical process/plant modeling and cost analysis methodologies Experience linking models across software platforms and managing coupled workflows Proven ability
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computational scientists to advance a next-generation, user-friendly, agentic AI platform for automated data analysis, interpretation, and user interactions. The appointment is expected to last two years and the
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