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-driven modelling, probabilities, and stochastic optimization solutions is an advantage. Excellent modelling skills and skills in scientific programming and/or numerical computing in languages like Python
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such as additive manufacturing, quantum material design, scientific data reconstruction, for material discovery, inverse methods, complex optimization, population and evolutionary dynamics, cyber security
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research leading to academic publications. The position is intended for a duration of 4 years. The optimal starting date for this position is September 2026. Profile As the ideal candidate for this position
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working, and provide space for supportive colleague communities via numerous employee resource groups (staff organizations). Our goal is for everyone on the Berkeley campus to feel supported and equipped
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks for numerous retail, restaurant and
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, and teach undergraduate and graduate courses in numerical analysis and scientific computing with applications in areas such as optimization, data analysis, discrete mathematics, and artificial
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AI-driven process control and optimization - CMOS-compatible fabrication and integration for electronic, photonic, optoelectronic, and quantum devices - Sustainability in semiconductor manufacturing
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 12 hours ago
contracts, procurement, and cost optimization to ensure transparency and fiscal responsibility Conflict Management: Proactively addresses workplace challenges with fairness and professionalism, fostering a
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on the fabrication, assembly, and testing of heat pipe systems Contribution to the development and optimization of manufacturing and integration methods for heat pipe components Numerical simulations (FEM/CFD
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We are seeking a highly motivated doctoral student to develop ship physics-integrated machine learning models for real-time prediction and optimization of wind-assisted ship propulsion systems