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Materials, mastering scientific machine learning, uncertainty quantification, and high-performance computing. Your models will inform fusion design and advance AI-for-materials. Perfect for physics, maths
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Electronics, will use computational simulations to study how thin films form during flowable chemical vapor deposition (FCVD), a process used to build advanced semiconductor devices. Unlike traditional CVD
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Are you an outstanding and ambitious engineering or computer science graduate looking for the next challenge? Do you want to work at the frontier of artificial intelligence and robotics to enable
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master’s degree in mathematics, theoretical computer science, machine learning, or a closely related field. Strong background in discrete optimization, algorithms, or reinforcement learning. Good programming
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-generation regenerative materials. This interdisciplinary project combines mechanical, materials, and biomedical engineering, offering training across fabrication, nanomechanical analysis, and computational
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explores how people of different ages play together, focusing on the experiences and perspectives of all participants. Working within a broader research program, the candidate will collaborate with
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within the project AI4TECS Writing a doctoral dissertation in computer science Publishing research findings in leading international conferences and high‑impact journals in AI, machine learning, and
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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Director of Studies (DoS): Dr. Yu Yao (yu.yao@plymouth.ac.uk , tel.: +447756140668) 2rd Supervisor: Dr. Maozhou Meng (maozhou.meng@plymouth.ac.uk ) Applications are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project...
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alters molecules and their properties, with focus on photoexcited states. The candidate will be member of the eT program developer team (www.etprogram.org) and developed models will be implemented