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Field
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that the programme will combine ideas from a broad range of disciplines, including machine learning, control theory, differential equations, port-Hamiltonian systems theory, modelling of power systems, digital signal
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- skills – experience: analytical skills, ability to demonstrate good knowledge in system modelling – simulation, (classical or modern) control theories or control applications with evidence Desirable
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Master’s in Robotics, Control Theory, Applied Math, or Mechanical Engineering eager to work on model-based control of soft robots Job description We are looking for a motivated PhD candidate to join the
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We’re looking for a motivated PhD student with a Master’s in Robotics, Control Theory, Applied Math, or Mechanical Engineering eager to work on model-based control of soft robots Job description We
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Your Job: Adaptive Control Theory (ACT) provides mathematically grounded and robust learning rules, prescribing that neurons should be diffusively forced toward a teacher trajectory and achieve
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, Robotics, Computer Science, Statistics, or related discipline. Strong background in Machine Learning and Control Theory. Demonstrated experience in research projects with industrial partners. Excellent
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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research environment. Opportunity to shape next generation control theory within a world leading research group and to collaborate with major energy sector partners. Access to Imperial’s high‑performance
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and applied research. Applied plant protection research is carried out in collaboration with industry and focuses primarily on the development of environmentally sustainable pest and disease control
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substrates while advancing our understanding of deep learning through dynamical systems theory. You will work with two cutting-edge experimental systems: (1) light-controlled active particle ensembles