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/adaptive algorithms, offline and online data analysis, conducting experimental research, and online evaluation of the developed adaptive strategies with a robotic application. The prospective students can
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intelligent sensing, followed by detection of the important events.In the light of autonomous decision making, the project aims at developing machine learning algorithms for knowledge extraction from data
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complexity, classical control techniques cannot be easily applied because of computational bottlenecks or an absence of suitable prediction models. Distributed control approaches have been conceived to handle
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algorithms that would allow the delay and/or suppression of hysteresis effects in dynamic stall through the use of control surfaces, for example, allowing the safe recovery of aircraft from post-stall
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using their high performance computational mechanics algorithm Alya, by coupling solid mechanics with electrophysiology. This project aims to personalise this model using medical images (MRI) collected
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Computational Astrochemistry/Algorithm development for Quantum Dynamics Calculations School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof AJHM Meijer Application
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Deadline: Applications accepted all year round Details The aim of this project is to develop scalable and efficient techniques and algorithms for localisation in different environments, based on data in
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adapted based on the abilities and needs of patients. Moreover, automatic intelligent algorithms will be developed in to make the control intuitive, natural and adaptive. Such that the model can learn new
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of the system is within the set at some time, then it is guaranteed to remain within the set for all future times. Therefore, being able to characterize and compute these sets is of prime importance when
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective