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to identify a model able to explain the presence of zonal jets. You will be based at the Dept. of Earth Sciences in Uppsala, but will be expected to travel both nationally and internationally. The position is
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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to dissect the differentiation and function of differentiated cytotoxic CD8+ T cells. These studies will be performed in human primary cells or cell lines, and potentially humanized mouse models, with goals
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look forward to receiving your application! We are looking for a PhD student in AI and machine learning with a focus on generative machine learning methods for cyber security applications. Your work
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fueling of hydrogen will be tested. These data will be used to validate the developed models and guide infrastructure design. You will collaborate with other PhD students and researchers from Uppsala
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safety. The goal of this PhD project is to increase knowledge of thermodynamic and material processes in marine hydrogen propulsion systems and to develop predictive models that ensure safe and efficient
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genetic, phenotypic, and environmental data, testing when and how evolution can be forecast. As a PhD student in our group, you will gain hands-on experience in computational and mathematical modeling and
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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look forward to receiving your application! At the intersection between AI and single atoms. Your work assignments We are looking for a PhD student with a background in machine and deep learning with
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areas, of which at least 30 credits must be at an advanced level. Courses in statistical analysis, quantitative methods, or mathematical models acquired outside these subject areas may also be included