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priorities. This may include: Supporting the design and implementation of community-led research projects. Conducting literature reviews and environmental scans. Assisting with data collection, analysis, and
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apply online for this vacancy and to view further information about the role, please visit: www.jobs.cam.ac.uk/job/53941 . For informal enquiries, please contact Professor Florian Hollfelder via
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health management (IVHM) system that leads to enhance safety, reliability, maintainability and readiness. Generally, prognostics models can be broadly categorised into experience-based models, data-driven
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the application you agree that your personal data will be shared among the participating institutions (University of Tubingen, University of Hohenheim, Senckenberg) for the purpose and over the duration
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: development of automated workflows for multi-omics data generation. In this project you will integrate small-scale automated bioreactors with workflows for the generation of high-quality multi-omics data
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the rich, unstructured information found in clinical notes and cannot effectively gather data on lifestyle and social determinants of health. This PhD project will pioneer a novel, hybrid AI framework
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in treatment receipt, time-to-treatment and treatment adherence will be assessed using linked data from the Clinical Practice Research Datalink, Hospital Episode Statistics and the Cancer Registry. In
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knowledge for sustainable formulation design. Using different data-driven feature representations, AI foundation models will generate chemical embeddings to predict key physicochemical properties. Coupled
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(sleep stage) classifiers based on the data available to implanted DBS systems, with the ultimate goal of enabling brain state optimised therapy. Specifically, this means developing sleep staging
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-weighted magnetic resonance imaging to comprehensively characterize the tumor microenvironment (TME). Tasks will involve the development of improved biophysical models and corresponding MRI data acquisition