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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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begore the deadline. The start date is 1st October 2025. This studentship is related to a multi-institutional EPSRC Programme Grant "AMFaces: Advanced Additive Manufacturing of User-Focused Facial
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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thesis within the contract period is to be expected. A PhD training program is part of the agreement and you will be enrolled in the Graduate School of the Faculty of Science and Engineering. Candidates
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
-based digital twin, which can predict the assortment and sequence of two-dimensional all-DNA motifs required for the engineering desired tessellation patterns at the nanometer scale. We will use available
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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should have or expect to achieve, at least a 2:1 (or equivalent) in any engineering degree programme, physics or mathematics. English language requirements: Applicants must meet the minimum
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, with minimal computational cost. By developing an advanced reduced order modelling framework, this project will empower engineers and designers to achieve more with less—delivering high-impact decisions
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University of California, Los Angeles | Los Angeles, California | United States | about 12 hours ago
after the review date will only be considered if the position has not yet been filled. Position description The Department of Computer Science in the Henry Samueli School of Engineering and Applied Science
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. The start date is October 2025. Are you passionate about applying computational science to real-world engineering problems? Do you want to develop digital twins of materials that can predict performance and