45 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" positions at Newcastle University
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equations to simulate pollutant transport, mixing and biochemical processes. To enable rapid prediction, a machine-learning surrogate model based on Gaussian process regression will be developed and trained
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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural
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systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural language understanding (to interpret instructions), and action generation (to respond), enabling robots
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, including but not limited to computer science, data science, engineering or mathematics, who are passionate about machine learning and AI research. Strong analytical thinking, problem-solving skills, and the
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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks
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properties of representative sediment classes. · Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning. · Assess the reliability
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properties of representative sediment classes. · Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning. · Assess the reliability
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on Arup’s AR4NBS initiative (Autonomous machines with subs - final delivery version - viewing copy - YouTube ). Number Of Awards One Start Date October 2026 Award Duration 4 Years Application Closing Date
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electricity and water to run washing machines. Improving the sustainability of these everyday processes is essential for meeting net-zero targets and reducing environmental impact. High-performance laundry
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, willingness to learn, and the ability to think creatively about complex physical systems are just as important as specific technical expertise. This PhD project—High-Fidelity Simulations of Geological CO2