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and workshops), and use these to data to develop a behaviourally informed toolkit which will likely include development and delivery of training, staff rewards, and other elements such as incorporation
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analysis of galaxy cluster number counts from SO and Weak Lensing from LSST, and the application of these methods to early data from both surveys. The second post will be focused on the combination of galaxy
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analysis, and experience of working with clinical data and Python-based tools. This is a unique opportunity to contribute to a project with direct clinical relevance, aiming to improve outcomes for children
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and ML techniques). We need to use large language model for an automatic design of the tower. We target to develop an AI-driven assistant ("AI-Copilot") to automate the complex design and analysis
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within A. fumigatus, as well as the design and running of long-term evolution experiments, requiring whole genome sequencing and bioinformatic analysis. Applicants should have a PhD (or equivalent) in
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will receive training in big data handling, genomics, statistical analysis and the interpretation of outputs generated. They will also play an important role in developing an operational pathway
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. This would be expected to include independently performing experiments utilizing transgenic animal models and the downstream isolation and analysis of immune cells using a variety of techniques including, but
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data analysis. Proficiency in advanced AI techniques will be essential, including foundation models, multimodal deep learning, generative AI methods, transformer architectures, and causal inference
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what lessons these hold for the wider region and the UK. The role will primarily include qualitative data gathering and analysis methods, including semi-structured interviews, workshops, focus groups and
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This is an outstanding opportunity for a Research Associate, with a background in deep learning and medical image analysis, to work within the reirradiation research team under the supervision of Dr