16 postdoc-in-automation-and-control-"Multiple" PhD positions at Cranfield University in United Kingdom
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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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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business needs while pushing technological boundaries. Your research will deliver transformative impacts across multiple industries by creating implementable solutions to longstanding operational challenges
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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aerospace, healthcare, and industrial automation. In safety-critical domains, such as aviation and medical devices, rigorous certification processes and continuous lifecycle monitoring are essential to ensure
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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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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
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trust in digital communications and readily bypass conventional security controls. This PhD research proposes to design, develop, and validate a novel, explainable, multi-modal detection framework. By