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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 2 months ago
to collaborate with experts from diverse fields including engineering, environmental science, policy studies, and business to address complex decarbonisation challenges. A life cycle based approach may be taken
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(IoT) device ecosystem. Despite the technology’s potential, however, flexible electronics face numerous technology challenges. This PhD project aims to tackle one of the most critical technology
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and upper stage launch systems. Simulation and test campaigns can be significantly costly in both time and cost having significant implications to technology hardware development. A software that allows
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policymakers. Entry requirements Applicants should hold or expect to achieve an equivalent of a first or second-class UK honours degree in materials science, physics, engineering, or a related discipline. The
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and Civil Engineering PhD Research Project Directly Funded UK Students Dr Marco Colombo Application Deadline: 30 September 2025 Details Are you ready to push the boundaries of engineering innovation and
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at engineering or technical managers to plan and execute project activities for hardware and software engineers. The guidelines and specifications will allow hardware and firmware engineers to develop proof
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this testbed available to users for testing hardware and applications. NPL will lead on the testing and security evaluation of the testbed and collaborate widely on the technology development. The student’s
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nature-based solution opposed to traditional ‘grey’ engineering, offer catchment-level solutions by using natural processes to slow and store water through a series of diffused interventions. Historically
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Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour