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computational prediction, mapping, and functional characterisation of promoter sequences. Demonstrated expertise in measuring plant photosynthesis and performing plant growth assays under both optimal and abiotic
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of the successful candidate will be to optimize the folding, stability, assembly, and functional activity of complex enzymatic systems in plant cells using both transient and stable plant transformation approaches
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: synthesising and combining results from existing model-based sustainability assessments (e.g. LCA, spatial and scenario analyses) to identify optimal transition pathways and to set out a forward-looking research
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optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative AI, or active learning for materials applications. Integration of theory and experiment: Using computation and
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advanced numerical simulation and/or optimization tools to the design and characterization of the facility; interact with other technical groups working on the Diamond-II design (e.g. Engineering
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to delivering optimal gout care, by conducting focus groups, stakeholder engagement work, and qualitative data analysis. They will support the development of interventions to address identified barriers
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optimization; bioprospecting for novel microbial hosts, enzymes, and metabolites to support sustainable biomanufacturing. (Bio)pharmaceuticals: Processing science and technology for bio- and chemical
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optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative AI, or active learning for materials applications. Integration of theory and experiment: Using computation and