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Field
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gaining deep insights, we aim to design catalysts that fully exploit alkali species, driving real progress toward a more sustainable world. As part of our team, with expert supervisors in catalyst design
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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techniques, would be an advantage. The ideal candidate will have a deep interest in the algorithms that power graphics and a creative mindset, eager to think outside the box and develop novel solutions
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an excellent publication (or papers in press or equivalent) track record in high quality peer reviewed journals. Evidence will be sought of a deep understanding of the applicant's previous fields of research and
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affordable for parents and nurseries. Training: Data Deep Dive: You'll analyse data from interviews/focus groups/questionnaires with nursery staff, parents, and health protection teams, uncovering social and
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skillset, deep industry insights, and a commitment to sustainability, fully prepared to drive the decarbonisation of aviation in diverse careers spanning industry, academia, government, and policymaking
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. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development
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climate and market “shocks”. We will gain a deep insight into assessment methodology, as well as identify opportunities/barriers for sustainable and resilient biomass production in future landscapes. A
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to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront