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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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, purification of protein complexes, analysis of protein-protein interactions including electron microscopy, and cellular biology techniques to examine the effects of bacterial membrane vesicles in primary immune
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learning techniques to address complex biological questions with significant societal impact. The position offers the opportunity to contribute to groundbreaking research that will advance our understanding
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project ‘The Cerebra Network’, funded by Cerebra. The Research Fellow will be split 50/50 between the two projects for the first three years (overall 1.0 fte), and then work solely on the Cerebra Network
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-relevant media, in the application of quantum information driven tools, such as tensor networks or convex relaxations, to the study of complex quantum systems Excellent command of English, both written and
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of sewer network and overflows to support effective management, and develop strategies to control pollutions at sources. The post will include delivering research outputs in the form of weekly reports
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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for the design, optimisation or verification of complex structures. A proven track record of using relevant techniques to carry out analyses, critical evaluations, and interpretations of data as relevant
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of seed gene networks”. This project aims to use reverse genetics, cross-species complementation and single cell next-generation sequencing approaches to investigate how the gene networks that regulate
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wireless access networks and intelligent edge infrastructure. You will be expected to lead the research on certain aspects of these projects while contributing to other aspects, including assisting with