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circumstances and is a postdoctoral role under SOC code 2119. The University of Stirling recognises that a diverse workforce benefits and enriches the work, learning and research experiences of the entire campus
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are included but clinical medical themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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across scales ranging from single bacteria, single host cells, 3D in vitro models to infected hosts. We have developed new imaging technologies to visualise the interface between the host and the pathogen
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tools, collaboration with project stakeholders, and engagement with the consortium and Defence and Security stakeholders. Technical Requirements: Strong coding skills with background in machine learning
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About Us Applications are invited for a clinical research fellow in Cardiac MRI to undertake clinical and research focussed on advanced cardiovascular magnetic resonance imaging under
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of foundation codes. Handling spatio-temporal statistics of forecast uncertainty will be a key consideration. This kind of downscaling with machine-learning methods is a rapidly advancing field and it is an