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approach for use with dry fibre forming and RTM manufacturing processes. Assess if a modelling approach can inform process control and optimisation, leading to a reduced part scrap rate. Build simulation
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curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model experimentation and training. Science of Deep Learning: Exploring mechanistic
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On Brain Disorders. The successful candidate will join us (fixed-term 3 years, 100% FTE contract of employment) to develop computational models of the neonatal brain, working on the intersection
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by Renew Risk Ltd. (https://www.renew-risk.com/ ), offering opportunities to work with real offshore wind farm models and industrial datasets while addressing real-world challenges in collaboration
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models, hydrological catchment models and the Water Resources model for England and Wales (WREW), a national-scale, simulation model. You will quantify national and regional water supply-demand imbalances
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the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition. This project aims to develop a novel FEA-based approach
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train 15 early-stage researchers to develop human-relevant neuroscience tools beyond animal models, advancing next-generation in vitro and in silico New Approach Methodologies for complex brain disorders
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in MVDC protection and the technological challenges of using MVDC for power distribution. Developing mathematical and simulation models of relevant study cases for the study of faults in MVDC systems
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) computational simulations to understand both the electronic states of enzyme intermediates and the transitions between them. As a joint studentship, around half of the project will be based in Manchester and half
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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture