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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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engineered animal models and state-of-the-art technologies, we investigate the mechanisms by which inflammasome hyperactivation drives autoinflammatory diseases and inflammatory bowel disease. We also study
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include: - Extension to radio and optical diagnostics to test different interaction scenarios - Extension to low mass binary interactions at optical wavelengths - Development of empirically motivated models
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and sustainability; Investigate and apply artificial intelligence and machine learning techniques, including large language models (LLMs), across CENSE’s scientific body in its five thematic areas
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remain resilient in a world of increasing climate uncertainty? This PhD project offers the opportunity to work at the intersection of climate change, food systems, and advanced optimization modelling. You
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field data, experimental data, and field experiments. Salary is $70,500 annually, plus benefits. Expected start date is mid-June 2027. For examples of our research, see our faculty pages: https
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responsible for pressure generation and the physical factors limiting eversion. Finally, the experimental data will be integrated into a biophysical model linking pressure, geometry, and tissue mechanical
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of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop
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be the head of the computing unit. About the project The primary research goal will be to create quantitative performance models that describe a range of numerical methods, parallel programming models
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integration of West Nile virus and avian influenza issues into a participatory multi-agent model developed for the prevention of zoonoses as part of the PREZODE ZOOCAM project. The assignment aims to produce