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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 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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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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method and to optimize this method for realistic high-performance computer calculations. Subsequently, this newly implemented method will be used in combination with embedding techniques to describe
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian The Energy Research Institute @ NTU (ERI@N) is seeking to hire research
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in process design and process optimization, including model development and numerical simulation (Matlab, Aspen etc.) of advanced adsorption processes such as TVSA and ESA (joule heating, inductive
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. Faculty cover a wide range of research topics and methods and belong to the top 10 ISOM research groups in Europe . You will be able to benefit from the department’s strong research focus and its numerous
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NAnoparticles by combining experimental and numerical approaches ), funded in 2024 by ANR – The French National Research Agency. Nanoparticle (NP) synthesis is a viable way of pursuing the production of next
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optimizing their functional behavior. The goal of this postdoctoral project is to carry out state-of-the-art experimental research on mechanical properties of HEA NPs with the intent of elucidating the link
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supportive colleague communities via numerous employee resource groups (staff organizations). Our goal is for everyone on the Berkeley campus to feel supported and equipped to realize their full potential. We
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advanced artificial intelligence/machine learning (AI/ML) solutions for fusion science and operations. Building and applying foundation models and surrogate models to speed analysis and optimize performance