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solving. Diverse research areas: Work on numerical models, analyzing large data sets, statistical methods and more in a unique scientific environment. Who Should Apply? Emphasizing the physical system
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data. Excellent written and verbal communication skills for technical reporting and cross-functional collaboration. Familiarity with experimental validation techniques for CFD models. Prior publication
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to the full extent. The objectives of this project are i) to quantify the carbon footprint of silage production under different management practices using data collected in farm audits undertaken across the UK
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data integration, cancer systems biology, and single-cell analysis, with strong links to clinical and translational oncology. Our work is based in the dynamic research environment of Heidelberg
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: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: 30.09.2029 Job ID: 4388 We are a team of researchers using operational and information-theoretic tools to gain insights into quantum foundations
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: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: 31.08.2029 Job ID: 4391 We are a team of researchers using operational and information-theoretic tools to gain insights into quantum foundations
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ADTKD diagnostics and clinical trials. What you’ll do You will work at the interface of laboratory and data science, and clinical genetics. You will: Establish and characterise the UK ADTKD-MUC1 cohort
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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atomisers. To ensure high quality measurement data, enabling meaningful correlations, measurements will be performed on a simplified prefilming geometry, with aero and hydrodynamic features representative
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population-based studies. Using data from 11 million vessel segments from over 200,000 CFPs, we have shown that retinal vasculometry can predict cardiovascular disease as well as established risk scores and