67 postdoc-distributed-algorithms positions at University of Sheffield in United Kingdom
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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
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. The ultimate goal is to develop theory and methods for the construction of low-complexity invariant sets, using computationally tractable algorithms. Funding Notes This is a self-funded research project. We
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finite element modelling to simulate the deformation of microstructures, novel crack propagation simulation techniques and scale-transition algorithms. The model will be informed and validated using full
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optimise the algorithms for optimal process control. The research will benefit from the available experimental facilities including laboratory-scale digesters, excellent analytical facilities, expertise in
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into account. Traffic models and filters are going to be investigated and developed dealing with the appropriate fusion of multiple sensor data. Both centralised and distributed traffic state estimate techniques
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/battery systems for distributed power generation. The balance of economics and performance of the system will be the main objective of the research. Computer modeling techniques will be employed in order to
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electron microscope combined with Digital Image Correlation and a microgrid technique to measure local strain distributions in the microstructure up to failure. This project will be run in liaison with Tata