440 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " Fellowship research jobs in United Kingdom
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& International Health is seeking to appoint a Research Fellow in Health Data Science (with a focus on machine learning) to NeoShield , a multi-country implementation research programme focused on neonatal sepsis
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of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical systems. Key Responsibilities Derive and analyse closed-form mathematical
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processing and statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; Work on sleep datasets
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, microbial cultures, and cleaning validation samples. Develop data analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities
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for light–matter interaction in hyperuniform disordered plasmonic structures, including electromagnetic modelling, optimisation of metal–dielectric–metal resonators, and physics-informed machine-learning
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities
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experience) in applied mathematics, physics or engineering, and strong, up-to-date specialist knowledge in analytical and numerical spray modelling and machine learning. Experience with OpenFOAM or similar CFD
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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for light–matter interaction in hyperuniform disordered plasmonic structures, including electromagnetic modelling, optimisation of metal–dielectric–metal resonators, and physics-informed machine-learning