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conferences and writing peer-reviewed papers. This PhD includes 3-6 months spent at the UK National Physical Laboratory (NPL), for research-led training on inferring CO2 emissions using atmospheric datasets and
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2:1 in Mathematics, Physics. Mode of study Full-time Start date 1 October 2026
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coherence, and non-Markovianity therefore become important both for fundamental physics and for eventual practical applications. In this PhD project, we will develop the theory for quantum-optical protocols
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simulations that will be validated against subject-specific data of the real outcome. This will be an iterative process, aimed at finetuning the simulator’s biomechanical parameters, to improve its predictive
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carbon uptake/release by the land biosphere, since each process responds differently to variability and climatic change. Novel atmospheric tracer measurements may provide new insight into GPP and TER
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in atmospheric temperatures. The increase in freshwater inputs into the ocean are likely linked to changes in biological productivity, either through the resulting physical changes to the water column
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to eruptive activity. These transitions pose significant challenges to hazard management (1). Physical parameters, such as the location, geometry, and size of the volcanic system, and their changes over time
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creating virtual replicas of physical homes, the project aims to monitor and optimize energy usage, personalize living environments, and strengthen security measures. This work requires a comprehensive
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computing and the use of GPU clusters. Entry Requirements Acceptable first degree - Computer Science/Physics/Maths The standard minimum entry requirement is 2:1. First class in bachelor degree or a master
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change will affect the air-sea fluxes of the major greenhouse-gases within a consistent physical and biological model framework. TRAINING This is a collaborative project between UEA, and the British