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Field
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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audio algorithm code base including noise reduction, acoustic echo cancellation, automatic gain control, voice activity detection, packet loss compensation and other audio enhancements Supporting Research
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for real-world deployment. Key Responsibilities: Develop algorithms for DAS signal processing, wavefield analysis, feature extraction, and interpretation across infrastructure monitoring, urban geophysics
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monitoring including geohazard detection such as sinkhole and subsidence. Key Responsibilities: Develop algorithms for passive seismology, seismic noise analysis, geophysical imaging, and seismic source
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identification through lab-scale and field experiments. Key Responsibilities: Develop algorithms for guided-wave analysis, response analysis, sensor fusion, and system identification using distributed and multi
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worked Monday to Friday. Flexible working will be considered. Contract type: Fixed term contract Fixed Term Period: For 18 months Research Assistant (if PhD close to completion): Full time starting salary
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modeling and AI. This position will include: Developing new Generative AI algorithms for developing intelligent agents in areas such as planning, exploration, perception, physical reasoning, and memory
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11th October 2026 Languages English English English The Faculty of Technology, Natural Sciences and Maritime Sciences have a vacancy for a position as PhD Research Fellow within Renewable Energy
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and optimisation-based methods for TN/NTN unified networks. The work will involve developing algorithms for resource allocation, network slicing, service orchestration, traffic steering, and performance
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, physical AI, and spatial AI. The RF will contribute to the development of innovative algorithms, data preparation pipelines, and experimental evaluations that are central to the Physical Vision Group’s long