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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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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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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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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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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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description Integreat - the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo invites applications for a doctoral research fellowship. The PhD candidate will work at the
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. The Research spans all areas of chemistry such as analytical chemistry, physical chemistry, materials chemistry, inorganic and structural chemistry and organic chemistry. The research projects are many from
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analytics Exploring and implementing federated learning and privacy-preserving AI approaches for distributed clinical datasets Collaborating closely with data providers, clinicians, and technical teams
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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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environment. Key research Objectives: AI Innovation (Taxonomic Identification): Developing and optimizing deep-learning architectures (e.g., YOLO) for the automated detection and classification of nocturnal