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-scale neural dynamics during cognitive tasks. The PDRA will develop cortically-embedded models of visual cognition that can interact with images and/or videos in a way that is species-specific. Extensions
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chromatography, accurate-mass MS, MS/MS and appropriate use of ion mobility where valuable. Plan and conduct TD-GC-MS analysis of volatile compounds from gauze samples. About You We encourage applications from
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or similar. Running social simulations with AI agents using platforms like Concordia or similar. Coding in Python or a similar language for simulation, visualization, and advanced statistical analysis (causal
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ethics, research integrity and handling research data). Evidenced flexibility and confidence to tackle a wide range of tasks, with an open, pro-active, creative, & problem-solving approach. Evidenced
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administration, participant recruitment, liaison with schools, and quantitative and qualitative data collection and analysis with young people and professionals. Tasks will include developing and conducting
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investigating the microbiological and immunological basis of noma. You will lead defined components of the bioinformatic analysis of shotgun metagenomic sequence data generated from oral samples collected from
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Patient Advisory Groups (PAGs), conducting qualitative interviews, running focus groups, designing and executing large-scale international surveys with quantitative data analysis, and collaborating
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. Information on the research activity of the lab is available at: https://www.rinaldi-lab.com/. The successful candidate will be involved with all aspects of the data analysis including design, experimental
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that are applied for proteome characterisation to a high degree of precision including sample preparation, LCMS and data analysis is also essential. Specialist knowledge in the discipline, proven ability to manage
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methods for the modelling and causal analysis of mass transit systems. The research will focus in particular on the development and application of data science methods to address key challenges in capacity