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quality modelling approaches to analyse the flow interactions between sewer discharge of surface runoff, as well as the dynamics of pollutants and pathogen propagations associated with water movements. The
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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity
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, multilevel and multidimensional measure of structural racism. The ideal candidate should possess a strong background in measurement theory and statistics, demonstrating mastery in structural equation modeling
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Location: Stirling Campus The Post Applications are invited for a Postdoctoral Research Fellow in the field of glacier modelling to work for a period of up to 36 months. The glacier modeller will
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evaluate field characterisation and monitoring data to develop geothermal resource models for individual project demonstration sites. About the person: Successful candidates need to: Have a PhD in Geology
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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of fungal pathogens. The successful candidate will make extensive use of a range of in vivo models of fungal infection and will have access to the wide range of transgenic tools and in vivo immunology
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evaluate field characterisation and monitoring data to develop geothermal resource models for individual project demonstration sites. About the person: Successful candidates need to: Have a PhD in Geology
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of fungal pathogens. The successful candidate will make extensive use of a range of in vivo models of fungal infection and will have access to the wide range of transgenic tools and in vivo immunology
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is a partner for the Alrek Health Cluster, Årstadveien, Bergen, and is supported by the Trond Mohn Foundation related to Complex Conditions and Ageing (CC.AGE). Read more about the project: https