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to partner laboratories to learn cell delivery methods, immunologic characterization of cells and tissues, live cell tracking, and multi-omics data analysis methods. As a PhD student, you devote most of your
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Computational Mathematics for reliable and trustworthy uncertainty quantification in science, engineering, and machine learning. Your workplace You will be employed at the Division of Applied Mathematics in a
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to machine learning is well funded and continuously publishes in high impact journals. We foster a creative working environment, where you will find freedom to implement, develop, and publish research
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(1–4) and in related projects. We encourage potential PhD candidates to visit our webpage to learn more about the research we are conducting. The PhD candidate is expected to be enrolled in two
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equitable teaching. The graduate school specialises in practice-based mathematics teacher education. This includes examining how teachers’ work is made into a learning objective in teacher education, and how
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the Arctic, experimental tests of climate driven changes in carbon export from land and turnover and release of greenhouse gases (CO2 and CH4 ) from headwaters, and use of machine learning and process-based
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learn experimental and computational approaches to tackle fundamental biological questions with medical relevance using innovative system-wide techniques. You will work on an exciting multidisciplinary
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of quantitative genetics and breeding. We do not expect the selected candidate to be proficient in all these from the beginning, but they should be eager to learn the required techniques. On a personal level, we
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a strong asset. Contract terms As a PhD student at Chalmers, you are an employee and enjoy all employee benefits. The position is limited to four (4) years, with the possibility to teach up to 10
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experimentally verified results is a necessary: Research Topics: Learning-Based Autonomous Systems for Field Robotics Reinforcement learning-based navigation Multi-agent coordination and communication-aware