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diverse expertise and collaborative partnerships to foster innovative and socially engaged doctoral research. The award supports new and emerging themes across art and humanities, architecture, design, and
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(CHF) phenomena – the prediction of which is key to safely designing and operating water based nuclear reactors. Current industrial modelling tools necessitate excessively conservative safety margins
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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
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under climate change, enjoy fieldwork and can lead the experimental design to contribute to meaningful and impactful research. You have a desire to close knowledge gaps in our understanding of the sea
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to co-design these avatars and training experiences. The goal is to create digital tools that help new or incoming carers feel better prepared for the specific behaviours, communication styles, and
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Data-driven predictions of dynamical systems are used in many applications, ranging from the design of products and materials to weather and climate predictions. Mathematical concepts from geometry
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harvesting complexes operate to enhance photosynthesis in plants. (3) Charaterisation of metallopeptide complexes for the design of more effective MRI contrast reagents. (4) Understanding of how structurally
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: Full Time Closes: 7 January2026, 23:59 GMT Application link: https://www.essex.ac.uk/postgraduate/research/doctoral-training-partnerships/aries ARIES (Advanced Research and Innovation in
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associated numerical methods and AI, will be used with High Performance Computing (HPC) to improve understanding of key flow physics and inform future HPT design. Skills and Experience Required: Applicants
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will build on ongoing work from the group in the design, synthesis and study of functional organic macrocycles and molecular capsules and their use primarily in catalysis, but also molecular recognition