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The SnT Automation & Robotics Research Group is hiring a motivated PhD candidate for the bi-national project DOMINANTS (Dexterity-Oriented Methodology in Optimized Design and Control of Soft Aerial
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and ground), and boasts expertise in controlling and deploying them in practice, as well as in designing coordination strategies for them. Our recent work on ML-based co-optimization demonstrates some
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position for candidates interested in interpretable AI, stochastic optimal control, deep learning and high-impact research in sustainable mobility. About us The position is located at the Systems and Control
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career, whether in industry or academia. Please contact Prof. Isaac Chang (Isaac.Chang@brunel.ac.uk ) for an informal discussion about the project. Eligibility Applicants will have or be expected
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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for growth and flux control. Engineering and optimization of microbial strains for production of bio-based products. Integration of metabolomics (targeted and untargeted), transcriptomics and proteomics
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Optimized Design and Control of Soft Aerial Manipulators), in collaboration with INRIA Lille Nord-Europe in France and its leading Defrost team in soft robot simulation and control, see https
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networks become essential to manage network requests, while maintaining high availability and optimal resource utilization. One PhD studentship is available for work in the area of Digital Twins for optical
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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be utilized to optimize the human comfort in combination with energy efficiency. The first part of the PhD will be the optimization of a web application used to control a smart floor of a building. The