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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning
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and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
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About us: We are seeking to appoint a postdoctoral research associate with an excellent track record in semantic technologies and machine learning. Topics of interest in this area include, but
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are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
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innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a complete in silico framework to accelerate the discovery
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to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and predictive analytics Good communication skills and
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for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data
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metabolism Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and
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, data normalisation and machine learning methods applied to biological datasets Experience with data management and version control (Git/GitHub, workflow automation, documentation) Capacity to work