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of mathematics, statistics, data science and physics to make real impact outside of academia and to interdicsiplinary research. NU Solve also operates a drop-in clinic for University staff to get help with
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railway earthworks. Additionally, the project will integrate environmental data through data fusion and develop automated machine learning tools for anomaly detection and risk assessment. The effectiveness
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third over the past 25 years, which is inferred from sparse soil data and the widespread decline of their avian predators. Recent developments in soil geophones and contact microphones have enabled
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- or tissue-microenvironment. Our existing collaborations with AstraZeneca have yielded very interesting data specific metabolites that are involved in the migration and positioning of regulatory (Tregs) and
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co-design workshops with men from Black backgrounds and lower income backgrounds, in communities across Yorkshire. You will lead data analysis within the team and help develop targeted recruitment
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Contract type: Full time (35 hours - 1FTE), fixed term (18 months) Detailed description The recruited candidate will be responsible for generating a database of qualitative data acquired through
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vehicles, data centers, etc.). These devices are mostly power electronic interfaced introducing new types of dynamic phenomena and the need for more detailed models, increasing complexity. In addition
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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complex input. For instance, in physics-informed ML, in addition to data examples used by a standard ML setup, domain knowledge serves as an additional input. It can be in an explicit form of rigorous
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will be secondary data analysis, linking reported incidents of violence with weather data to identify correlations between climate variables (e.g., temperature extremes, humidity) and violent crime