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interactions. Machine learning: reinforcement learning, or multi-agent systems. Signal processing: spectrum sensing, localization, or radio environment modelling. Multi-agent systems: distributed intelligence
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biomedical applications. This project will involve studying the structural properties of lipid nanoparticles, modifying particle stiffness by changing their composition and self-assembly process. The
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PhD Scholarship in Integrated Photonics for Telecommunication, Biosensing and Precision Measurements
waveguides and fibres Digital signal processing Design and analysis of photonic systems. Applicants must have a Bachelor/Masters degree (or equivalent) in electrical/electronic engineering, nano
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advanced materials and printing methodology enabled sustainable process for elastomer compositions for tyre treading that will enable efficient and reliable renewal of tyre in short time by machine
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The aim of this project is to describe ion conduction and activation/inactivation processes by employing molecular dynamics and statistical mechanical methods. The expected outcome is an improved
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computer simulation methods to explore the mechanisms of ion conduction, selectivity and activation for ion channels that control neuronal signalling and brain function. Investigations may extend to how
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the following knowledge and/or experience are highly preferred: Computer Vision, Signal Processing, Machine Learning knowledge and/or; Experience Industry knowledge and/or; A track record of published
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system quality) to operationalise the development process of such systems. A grand open challenge is to make these frameworks more complete by including new aspects such as fairness that are as important
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of surfaces, which is currently not resolved issue to stop bacterial colonisation. Magnetic control of nanoparticles will be relevant across several biomedical imaging techniques. Application potential: anti
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The PhD candidate will gain intensive knowledge in innovative processing protocols for chemical sensing and to develop data acquisition system with the Machine Learning (ML) and/or Deep Learning (DL