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analytics, geographical information science, satellite positioning, ubiquitous positioning, photogrammetry and remote sensing, geodesy and geodynamics, environmental monitoring, geo-hazards studies
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conferences Your profile - Master?s degree in physics, mathematics, computer science, or a related field - strong analytical skills and solid theoretical background - experience in machine/?deep learning and
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position: Deep learning for phase-contrast synchrotron X-ray tomography Reference code: 2026
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an analytical-computational framework for a “living” 4D Digital Twin (3D + time) to enable automated progress monitoring and multi-domain safety assessment in civil engineering applications. The project focuses
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training programme at the start of the PhD to develop skills in areas such as programming, data analysis, machine learning and signal processing. This will provide the technical foundation required to work
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Biotech Campus (Sand Hutton), with short visits to Newcastle for training and technology transfer. Fera Science Ltd is a world-leading analytical laboratory with a strong track record in developing and
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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning
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technology transfer. Fera Science Ltd is a world-leading analytical laboratory with a strong track record in developing and deploying cutting-edge diagnostic technologies, including qPCR, LAMP, and high
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About the Project As federated learning systems become increasingly embedded in high‑stakes domains where data cannot be directly shared, such as healthcare and finance, the ability to selectively
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design to improve on-site waste management The development and implementation of initiatives that enhance waste sorting quality and documentation practices The application of analytical, computational, and