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Field
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contributing positively to a collaborative research environment. Desirable: experience with building energy or power system applications, cooperative or coalitional game theory, or high-performance computing
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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reflection. Our previous work has only just reached the point where all the above elements have been successfully combined [1-2]: a working multi-scale design process combining theory and numerical simulations
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Application deadline: All year round Research theme: Control systems and theory, Applied Mathematics How to apply:uom.link/pgr-apply-2425 Number of positions: 1 Open to: UK This 3.5 year project is
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Master’s degree (or other equivalent experience). Suitable backgrounds for these PhD positions include, but are not limited to, power engineering, industrial engineering and operations research, mathematics
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leverage advanced bespoke continuum robotic systems to demonstrate the feasibility of applying the proposed coatings can be deployed in-situ. Ultimately, this work bridges the gap between the theory
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. Ultimately, this work bridges the gap between the theory of advanced material science and the challenges of implementation in an industrial environment. This research contributes to advance the fundamental
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. •Detailed semantic understanding of operational environments for Machine Situational Awareness, particularly within contested, congested and degraded scenarios. •Fully autonomous robust intelligence data
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Modulo Theories) solver. The work aims to demonstrate methodology through the application of the prototype to a real-world industrial system (provided by our industrial partner - Evolution Measurement
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If you would like to solve real-life problems using statistics and operational research to have positive impact on business, the economy or society, then consider applying to the STOR-i Centre