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intensifying upper ocean mixing processes. However, major gaps in our understanding remain due to challenges in observing and modelling the Arctic Ocean. Research Methodology The aim of this project is to
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Schlumberger Foundation Faculty for the Future Fellowships 2026-2027 is open now. These are the requirements to apply for a fully-funded PhD or Post-Doctoral Fellowships in STEM (Engineering
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
We are pleased to announce a self-funded PhD opportunity for Quantitative assessment of damage in composite materials due to high velocity impacts using AI techniques. Composite materials, such as
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project called Policy Modelling for Health. This fully funded PhD place provides an exciting opportunity to pursue postgraduate research in population health modelling, estimating health outcomes and health
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experimental chemistry. Additional training in a wide range of soft and hard skills is available at the University. What you will do: This PhD project aims to bring together multi-scale modelling and data-driven
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1-dimensional ocean-ice model. You will identify any long-term changes in ocean CO2 uptake along the Antarctic Peninsula using data from Rothera, SOCAT (www.socat.info) and mapped CO2 products, while
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PhD: Digital Optimisation of Rail Grinding EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering for Manufacturing PhD Research Project Directly Funded UK Students Dr
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: adapting existing models of bird movement and migration to test hypotheses about the ecological processes shaping observed connectivity patterns. Identify species and populations that have the highest
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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon