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background in mechanics and computational engineering. Demonstrated interest in the physics of sea ice and computational modelling of ice will be considered as an advantage. Suitable backgrounds include
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Computational Fluid Dynamics (CFD), fluid mechanics, and Artificial Intelligence (AI), with a particular focus on developing deep reinforcement learning methods for active flow control of hydraulic
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studying the effects of defects in composite structures. About us The Doctoral student position is placed at the Division of Computational Mechanics and Materials Engineering , which belongs to the
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professors and a group of doctoral students and post-doctoral researchers. Your experience and ambitions We are looking for a candidate with a strong background in mechanics and computational engineering
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at the Division of Computational Mechanics and Materials Engineering , which belongs to the Department of Mechanical Engineering . We foster an inclusive, friendly, and helpful work environment to
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(preferably) in Mechanical Engineering, Materials Science, Civil Engineering, Computational Mechanics or equivalent You are fluent in English, both in speaking and writing You have strong
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Your Job Analyze the intrinsic many-body dynamics of noisy and monitored quantum circuits, mapping them onto statistical-mechanics models Develop analytical approaches (e.g. replica methods and
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-resolution analysis at fatigue-prone hot-spots while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress
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STFP Home sign in | focus RAP opportunity at National Institute of Standards and Technology NIST Development of New Computational Methodologies for Molecular Simulation of Soft Materials
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-changing careers. Learn more about Sandia at: https://www.sandia.gov *These benefits vary by job classification. What Your Job Will Be Like: Looking to advance the frontiers of research in computational