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application of conditional diffusion models, flow matching techniques, or related generative approaches, as well as experience working with probabilistic (Bayesian) methods and statistical modelling. Strong
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infrastructures. A solid background in beam dynamics in synchrotrons and the corresponding numerical modelling is required. Applicants should have the ability to identify research objectives and subsequently
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the molecular structural dynamics and embedded chiral information in redox-active polycyclic aromatic hydrocarbons influence the emergence of novel photoluminescent properties. While the majority of objectives
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or mechatronic design and analysis • Ability to work as part of an extended team in multiple disciplines and locations • Ability to identify research objectives and subsequently conceive, plan and
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form; ability to work as part of an extended team in multiple disciplines and locations; ability to identify research objectives and subsequently conceive, plan, and independently execute appropriate
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period of up to 6 months. The is funded by the Department of Chemistry, Oxford University, aligned with its Strategic Research Funding in Sustainable Energy. *Find out more about the research and group
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McGonigal group, see our recent papers 1 , 2 , 3 . The position is funded by UKRI. Find out more about the McGonigal research and group here . About you Applicants must hold a PhD in Chemistry or a relevant
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also be able to undertake research based on their academic expertise on specific themes and objects in the exhibition and accompanying catalogue. This is an excellent opportunity for an advanced doctoral
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learning phase-picking models, combined with advanced phase association, probabilistic earthquake location, and relative relocation methods, to significantly enhance earthquake detection levels and location
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expression as well as HDX mass spectrometry and is funded by BBSRC. Find out more about the research group here . Applicants must hold a PhD in Chemistry or a relevant subject area (or be close to completion