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manufacturing. You should have interest in or experience with data-driven methods, including machine learning, Python programming, or data curation. Regular reports of research progress are required and research
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. You will also be responsible for implementing the model as a computer simulation and analysing it within a health-economics framework using standard computational techniques. You will also be
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10 minutes and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre
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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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time role, 0.1FTE. The activities of this role will support development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning
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machine learning. Supervision will be provided by Prof. Ali Mazaheri, as well as Prof. Fang Gao Smith, and Prof. Helen McGettrick. The successful candidate will have a strong background in psychology
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, computational biology, computer science, data science or a related subject area and proven knowledge of python programming, developing machine learning/AI based tools and HPC. You will be expected to work as part
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communication journals Demonstrable proficiency in advanced quantitative data analysis: applied machine learning, statistical analysis, and handling complex data. Programming skills in Python and R are essential
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developing ideas for application of research outcomes. This post also be linked to research activities linked to the Faculty’s research platforms such as the Power Electronics, Machines and Control Research
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quantitative and digital methods, such as descriptive/inferential statistics, data modelling, machine learning (ML), experimental prototyping and technology ideation. A significant degree of autonomy is required