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quantum systems can range from Markovian (“no memory”) to non-Markovian, where information is exchanged in both directions between system and environment. The relationships between light emission, quantum
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experience with experimental design, eye-tracking, data analysis, and coding (e.g., R, Matlab, Python) are highly desirable but not essential. The project will be supervised by Dr George Malcolm and the
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bio-optical (fluorescence and backscatter) data from a 2025 research expedition to the Bellingshausen Sea, West Antarctica, coupled with data from laboratory analyses of algal pigments, particulate and
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Project Supervisor - Dr Stefano Landini The rapid evolution of electric vehicles (EVs), data centers, and high-performance energy storage is driving the need for battery systems that manage heat
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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, are crucial for modelling volcanic processes and are vital for understanding the transitions. Geophysical monitoring provides essential information to constrain these parameters and inform decision
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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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. Describe site connectivity along global flyways, using a global dataset of important areas for seabirds (i.e., Key Biodiversity Areas) and data from the STD. Investigate the drivers of flyway connectivity
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, the research aims to enhance responsiveness, efficiency, and scalability. Leveraging the ultra-reliable, low-latency communication and high data throughput enabled by 5G networks, the study seeks to facilitate
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interventions. These insights may ultimately lead to the identification of new targets for the development of therapies for ageing and age-related disease. For more information please contact: rebecca.c.taylor