78 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof"-"Prof" positions at Cranfield University
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clearing and resetting meeting rooms when required. Serve occasional drinks in the bar after hours, on request to the required standard. Prepare occasional late night menu options to the correct standard
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conducted in the IWT. Disseminate research through publication in high-quality journals and leading conferences. If possible, develop or adopt numerical simulation models and methods pertinent to icing
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spatial mapping approaches to join our team of academics working on decision support systems to improve schistosomiasis preparedness and control during development of water management infrastructure. We
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project will develop novel methods for modelling and controlling large gossamer satellites (LGSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. The candidate will
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We invite applications for a self-funded PhD to explore innovative research in the development of human-centred embodied multi-agent systems that able to compensate and augment human capabilities in
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focuses on developing an innovative ground-based robotic inspection system using thermographic Non-Destructive Testing (NDT), a critical method for ensuring aircraft safety and reliability. NDT is
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
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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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of complex metagenomic data. You will also become proficient in lifecycle carbon accounting and data-driven decision-making, all mapped to the Researcher Development Framework at Cranfield University. Regular
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine