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to contribute to a collaborative, interdisciplinary research environment Are eager to learn and explore new ideas at the intersection of ML and optimization Can program efficiently in one or more languages
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
optoelectronics, light emission, optical sensing and quantum communications. This is an ambitious research program, with a strong interdisciplinary nature, across photonics, plasmonics, device physics, electrical
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- looking. Sensor technology plays a key role in this transformation, enabling real-time monitoring, automation, and intelligent decision-making. Despite these needs, many water treatment processes still rely
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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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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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enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a leading technical university globally recognized for the excellence
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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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Degree PhD Course location Potsdam In cooperation with The innovative PhD and postdoctoral programme is offered in conjunction with the Faculty of Digital Engineering, a faculty jointly founded by
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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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. 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