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-developing the principles (e.g. ethics) and methods for anonymising, processing and analysing sensitive data collected by a national charity’s 24/7 helpline for people experiencing or witnessing elder abuse
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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supervisors and fellow researchers, you will contribute to the development of solvers for combinatorial optimization problems and apply them to real-world data from industrial partners. As part of your PhD, you
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of testicular tissue Validate gene expression at the protein level via IHC and Western blotting Analyze large-scale transcriptomic data (R, Python) Test allele-specific regulatory activity using luciferase
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its processing capabilities but also its adaptability, leveraging early developmental data and ecological validity. Infant data will be acquired in collaboration with Dr. Tessa Dekker (University
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considers the transport of suspended matter (tracers); calibrating and validating the model against long-term data on hydraulic conductivity, water temperature, and dissolved oxygen from several rivers
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biological data, development of deep learning and large language models for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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significantly impact next-generation experiments at large facilities. Tasks: This project will develop innovative ultracold neutron detectors, using superconducting microstructures for spin- and energy
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, and mortality. This will be achieved by linking large existing datasets that contain data on people with diabetes foot disease in the community (such as Diabetes Registries, Diabetes Foot Registries