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Title: Assistant or Associate Professor of Mechanical Engineering: focus in mechanics of materials aiding in the design and optimization of advanced manufacturing processes. Employee Classification
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various aspects of QC ranging from quantum chemistry to optimization and machine learning topics. We offer interested students to participate in this cutting-edge research via master thesis projects in
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Process-aware optimal design of polymer Additive Manufactured (3D Printed) components via hybrid layout and topology optimisation School of Mechanical, Aerospace and Civil Engineering PhD Research
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appears spontaneously at a structural phase transition. In this project, we will focus on identifying strategies to optimize the energy-storage performance of anti/ferroelectric materials based on HfO2
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This is an exciting fully-funded studentship (with a stipend of £18,800 p.a. plus full tuition covered for a 3 year period) under the ‘Cranfield Industrial Partnership PhD Scholarships Scheme’ (CIPPS). This PhD is designed to investigate a lighter, next generation alternative material to reduce...
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In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
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Department of Applied Mathematics Assistant Professor in Applied Optimization and Operations Research / Data Science and Analytics (Ref. 241106015) The Department of Applied Mathematics (AMA) offers
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« department, we deal with technologies, processes and methods for optimizing production processes as well as quality assurance in manufacturing. In the »AGILEHAND« research project funded by the European Union
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: Applied Optimization and Operations Research / Data Science and Analytics / Applied Statistics and Financial Mathematics / Engineering and Computational Mathematics / Mathematical Science Appl Deadline
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Master Thesis on Bayesian Optimization of Multi-stage Processes with Smart Inducing Point Allocation
to shaping the future. Would you like to gain experience in a modern and professional team and see first-hand how research and development in the field of process optimization using probabilistic AI works