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Field
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learning based synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation, as well as new measures of privacy and fairness to be used
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Engineering or related topic. Working experience and knowledge of nonlinear numerical modelling of structure and infrastructure exposed to multi-hazards conditions Working experience of advanced programming
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these three main questions: 1 - How do stars form and evolve? 2 - How do stars evolve in isolation; in multiple systems and as a population? 3 - How does atmospheric activity (e.g., stellar winds, flares
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and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary conditions for a rewarding career
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focused on using spatial profiling and machine learning of human specimens in combination with functional experiments in animal models to understand cancer initiation, progression, and metastasis. We
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the Ofoten Line and new initiatives associated with the Arctic Test Arena project. Railway infrastructure in Arctic and Nordic regions is increasingly exposed to harsh weather, heavy traffic loads, climate
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priorities Experience with thermo-physiological modelling (highly regarded) Survey design and implementation experience will be advantageous Experience in firefighting and field work (highly regarded
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models: in vivo mouse models of trauma, hemorrhagic shock, or critical illness ● Multiomics: proteomics, metabolomics, lipidomics, or bioinformatic data analysis Conditions of Employment
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. You will have, or be close to obtaining, a PhD in the field of Atmospheric or Climate Science, or a related discipline, and have experience of running global climate models on high performance computing
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academic and industrial expertise in epigenetics, mathematical modelling and high-resolution stable isotope labelling based analysis of the dynamics of metabolic cofactors and post translational