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can be leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models
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Work within specified research grant Operate within area of specialism Collect and organise research data held primarily by the Bank of England Archive, while making visits to other relevant UK archives
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if required Contribute to writing bids for research funding Analyse and interpret data Apply knowledge in a way which develops new intellectual understanding Disseminate research findings
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, with opportunities to build an international research portfolio. The post holder will work on developing and testing study design and data analysis methods, particularly related to cluster randomised
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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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responsible for the entire project from polymer synthesis, crystallisation-driven self-assembly, characterising data collection interpretation. Training will be provided in all of the component techniques but
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themselves in the HPB medical oncology team to help deliver clinical care and trials and also integrate themselves into a research group at the university where they can generate preliminary data. Within
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goals of the project, in collaboration with Dr Andrew Plackett. Collect research data through laboratory-based scientific experimentation and (where necessary) literature reviews. Analyse and interpret
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supervision Conduct qualitative data collection, including semi-structured interviews and/or focus groups Analyse and interpret qualitative data using appropriate methods (e.g. thematic analysis) Use
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Collect research data via experiments carried out on the analysis and recycling of Li ion battery materials Supervise students on research related work and provide guidance to PhD students on the Li ion