40 development "https:" "https:" "https:" "OsloMet storbyuniversitetet" PhD positions at Cranfield University
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. Focusing on adaptive intelligence, which blends human creativity and machine intelligence, the project will develop Multi-Intelligence Agents (MIAs) to facilitate the seamless integration of social factors
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Cranfield University is excited to invite applications for a PhD studentship focused on developing and validating innovative origami-paper eDNA sensors with community scientists for the rapid
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-disciplinary approach that integrates design, technology and management expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base
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Join us for this exciting self-funded PhD studentship on " Development of Sustainable and Cost-Effective Coatings to Mitigate Battery Thermal Runaway Propagation" in collaboration with
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research opportunity focuses on advancing large-scale additive manufacturing using metal wire as feedstock and electric arc as the heat source. The project aims to develop an innovative and efficient method
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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the likelihood of the target to fall within the stationary clutter returns and in the shadow of complex structures. We will investigate the use of multistatic radars against low observable threats and develop
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to the conventional total pressure rake and measures the full three-components of velocity. The aim of the project is to develop, and exploit, an approach to synchronously measure the velocity and total pressure flow
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supply chain resilience. Following a PhD‑by‑papers route, the research aims to deliver three high‑quality scholarly outputs and develop insights to enhance supply chain management practise. This project
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens