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, machine-learning tools, and Lagrangian transport modelling. You will be based at the British Antarctic Survey and work closely with experts at the University of Leeds and Exeter, who provide cutting-edge
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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contribute significantly to these growing fields. This PhD position is ideal for candidates interested in the following areas of machine learning: Geometric learning: exploiting the structure of data (e.g
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to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional
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, or computer science A PhD or equivalent professional qualification and/or experience in the field of machine learning for biology and mathematical modelling Strong planning and organising skills Excellent written and
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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep
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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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certification, dramatically accelerating innovation cycles. What you will gain: Expertise in Finite Element Analysis, Scientific Machine Learning, Uncertainty Quantification, and Professional Programming
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Accessible Tinnitus Notch Noise Therapy via Machine Learning, Acoustic Metamaterials and Additive Manufacturing (with NHS and TinnitusUK) EPSRC Centre for Doctoral Training in Sustainable Sound
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the state-of-the-art wind tunnel facilities of the Department of Aeronautics, and will utilize novel theoretical and machine learning tools. You can expect to become an expert in aerodynamics and turbulent