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balance in the workplace. The Faculty recognises that applicants may seek flexible working patterns which will be considered as part of the recruitment process. please see our working with us website page
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toward IgG substrates. Computational insights will guide the design of chimeric glycosyltransferases that incorporate Fc-binding domains to achieve proximity-driven enhancement of glycan processing
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process. For further information including key benefits designed to help maintain and support employees' well-being and work-life balance, please see our working with us website pages.
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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. What You’ll Do: innovate: develop scalable RPLD processes to fabricate REDS active mirrors collaborate: work with a dynamic team and engage in interdisciplinary research experiment: gain hands
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a new class of active mirror to underpin the next generation of thin-disk lasers. What You’ll Do: innovate: develop scalable RPLD processes to fabricate REDS active mirrors collaborate: work with a
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-ground processes and pollination. The research combines controlled experiments, advanced measurement and multiphysics modelling, and will generate open datasets and workflows to catalyse the emerging field
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designed to fulfil the requirements for an out-of-programme experience for a specialist trainee in oncology, haematology surgery, pathology or any other disciplines related to cancer, but may also be
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may play in stress responses, below-ground processes and pollination. The research combines controlled experiments, advanced measurement and multiphysics modelling, and will generate open datasets and
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, and catalytic processes. The project will use molecular dynamics simulations to understand molecular mechanisms of metal-based antimicrobial systems and biomolecular interactions, supporting the design