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Field
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Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and analysis of large-scale 2D/3D scientific data
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projects are devoted to in-house algorithm and code developments driven by leading-edge scientific challenges and needs. The NanoSIMS lab is specialized for studies of presolar grains and ancient planetary
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algorithm and code developments driven by leading-edge scientific challenges and needs. The NanoSIMS lab is specialized for studies of presolar grains and ancient planetary materials. ASIAA has a dedicated
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optimization algorithms (e.g., SAT solving, constraint solving, MaxSAT, SAT modulo theories, Answer Set Programming, (Mixed) Integer Programming, ...). We offer a fully-funded postdoc position, initially for 12
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methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 3 hours ago
of materials Proficiency in multi-physics FE simulations, topology optimization, and working knowledge of machine learning (ML) algorithms Demonstrated exceptional problem-solving abilities, a passion for
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pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group
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science, mathematics, computational physics/chemistry or equivalent. The candidate: must demonstrate expertise in algorithmics/machine learning/artificial intelligence must show motivation in the interdisciplinary
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Requisition Id 15448 Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large
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optimiser that accelerates both workflow efficiency and materials discovery. Main Tasks and responsibilities: Own the optimiser: design, implement, and tune heuristic/metaheuristic algorithms (e.g