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and to acquire valuable research experience. The PhD Project Life in the Greek-speaking cities of the Eastern half of the Roman Empire was infused with cultural interactions and the rich and pluralistic
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to data-driven research projects focused on glaucoma, diabetes or nAMD using large-scale clinical and imaging datasets. Develop, validate, and implement machine learning models and statistical tools
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(crowding, concentration of nutrients, size of liposome, etc.) with gene expression levels across a synthetic genome. To achieve this aim, you will use VASA-seq and Ribo-Seq to generate large data sets
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Supervisors: Dr Raj Pandya, Prof. Nicholas Hine, Prof. Reinhard Maurer While we as humans are used to seconds and hours, electrons and atoms in materials move a whole lot faster around a million
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diagnosis, and knowledge of the operation of helicopter systems. • Confident handling of Python and common data science tools. • Knowledge of high-performance computing and machine learning. • Fluency in
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tools. * Familiarity with tensorflow and/or pytorch. * Demonstrated ability to design and implement machine learning techniques and algorithms. * Demonstrated expertise in the Linux computing environment
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised
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PhD Scholarship in Big Data and Analytics for Crop Genetics Modern agriculture and biomedical research are driven by the availability of big data and the development of data science. The recent
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machine learning technologies. This PhD position is part of the project “Artificial Intelligence for the automated creation of multi-scale digital twins of the built world”, which is funded via the Georg