44 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation"-"Simons-Foundation" positions at Cranfield University
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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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-to-energy plasma unit capable of producing synthesis gas for electricity and heat. The innovation builds upon original research and integrates multiple stages (plasma gasification, slag recovery
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pressure to reduce both energy demand and chemical consumption. Project SandSCAPE, an Ofwat-funded programme, tackles this challenge by integrating purpose-built robots that skim slow sand filter beds while
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collection setup and data acquisition. •Training in ecological field identification. •Initial model training and software prototype development. Year 2: •Expanded image collection across multiple sites. •Model
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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that can be validated with experiments and bottom-up models at multiple scales in order to predict the macroscopic response. Hence, this research will investigate the degradation of metallic materials under
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via joint activities with EU and UK cybersecurity hubs, preparing you for careers in trusted electronics, AI security, and national critical infrastructure protection. Graduates from this programme will
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
optimization. The research focuses on creating efficient design workflows, validating multiple additive manufacturing approaches, and developing scalable production methods that can support global deployment
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scintillator-based radiation sensors combining multiple materials with complementary functions, offer a promising route to overcome these limits and achieve unprecedented timing resolution (sub-70ps), enabling
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient