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the PhD student in high-performance computing, computer programming, applied mathematics, fluid mechanics, mathematical modelling and data analysis for large datasets -of the order of 100 Terabytes
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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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create a working framework that includes both experimental and modelling prototypes, including AI/ML tools to assist with the large number of variables involved. This project is seeking candidates with a
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will generate a wide range of contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models
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that require treatment while reducing unnecessary detection of slow-growing cancers. You will play a key role in a large mixed methods project as a qualitative researcher conducting focus groups, interviews and
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Boreal forest recovery after clear-cut: We are looking for a highly motivated PhD student to collect data on and model hydro(geo)logy and greenhouse gas exchanges of boreal forests after
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, the supervision team have obtained data access to indoor environment sensor data at national scale from a leading industrial collaborator. To pair with this big dataset, outdoor environment data at MetOffice can be
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datasets, therefore, there will be a focus in the implementation of models for large volumes of data. The project will work in an exciting interface of statistics and machine learning and has the potential
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This is an exciting opportunity to explore the role of complex microbial communities in promoting resilience and maximising yields in large scale algal bioreactors exposed to different environmental