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-tuning only a small set of low-rank matrices for each agent role, drastically reducing GPU memory and training time while preserving the model's pre-trained knowledge. The primary outcome of this research
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mechanics. Skills you’ll gain Under the supervision of Charlie Heron and myself you will gain: Expert knowledge of centrifuge modelling challenges and solutions. Advanced programming/data analysis skills. How
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of experimental modelling challenges and solutions. Advanced programming/data analysis and simulation skills. How to effectively communicate complex and novel research. Opportunities to develop lab demonstration
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, GNSS positioning is highly susceptible to errors from atmospheric distortions, multipath effects, and receiver noise. Recent advances in deep learning have shown that data-driven pseudorange correction
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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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(R1) Positions PhD Positions Country United Kingdom Application Deadline 3 Dec 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan
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multimodal data, ultimately uniting rigorous machine learning foundations with biological discovery. Project details This PhD project will contribute to the development of generative models for multimodal data
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real-time rerouting recommendations. Beyond the PhD, the project’s data-driven models will evolve through continuous real-world updates, contributing to sustainable aviation practices and climate-aware
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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/position/type of hardware. Cranfield overview and Sponsor Information/Background: We have a long history in space systems, having undertaken space studies since the 1960s. Our current research has