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Field
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metabolic disease, including type 2 diabetes (T2D), Non-alcoholic fatty liver disease (NAFLD) and obesity, collectively referred to as metabolic syndrome (MetS), has occurred in parallel with a global decline
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detection model to a more flexible unequal-variance model in a hierarchical Bayesian approach (Lages, 2024). Techniques used: Computational modelling, Bayesian inference, sampling and simulation techniques
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functional outcomes. In parallel, you will develop new sensors for intracellular potassium concentration leveraging AI based protein design algorithms. Techniques used are Biomolecular NMR spectroscopy and
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well as community function, to be investigated in parallel. Standard geochemical analyses will be simultaneously performed to investigate interactions between the major nutrient cycles, and their impact on
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team. Work towards achieving the Objectives will run in parallel through the project, broadly along the following timeline: Year 1: literature review, desk-based mapping, initial fieldwork mapping and