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Field
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clinical engagement. This is a pivotal, significant and complex leadership role representing an opportunity for an exceptional individual who can combine their academic leadership and commercial acumen
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microbial communities: Microbiome engineering for a Net Zero future”. This project is led by Professor Sophie Nixon at the University of Manchester, in collaboration with the Earlham Institute. In
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an integral member of a leadership team within a specific faculty or professional services group, where you’ll lead complex people-related programmes, providing expert guidance on organisational change and
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experiences in simulation-based experiments in networking research Strong mathematics background for optimization and analytical modelling of complex systems Programming languages including C++/Python and
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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that will influence global environmental policy and industrial practice. You will be instrumental in building and maintaining relationships that extend Queen's international research network while managing
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), electrophysiology (EEG), interventional (TMS, tDCS) and neurocomputational (machine learning, reinforcement learning) approaches to understand the network dynamics that support learning and brain plasticity
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long-term sustainability. 9. To play a lead role towards creating and enhancing strong working relationships across internal and external stakeholders, national TRE networks, industry partners, and
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or postgraduate level, commensurate with career stage in one or more of the following curriculum areas: Mathematics Data Science Machine Learning Statistics Ability to communicate complex information effectively
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indoor cycling classes. Relevant recent experience of working and operating within a busy fitness complex (including free weights). Good working knowledge of Health & Fitness including the delivery