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The successful candidates should have the following qualifications: A PhD in Environmental Toxicology, Chemical Engineering, Environmental Chemistry, Materials Science, or closely related fields. Solid
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verification. runtime analysis and reconfiguration of in-vehicle TSN networks. Co-supervise MSc and PhD students. Optionally contribute to teaching and proposal preparation. Required qualifications: As a formal
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research in peer-reviewed journals and presenting at international conferences We are looking for a candidate with: A PhD in oceanography, climate science, applied mathematics, computational science, or a
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project, “Mathcrete”, and offers a unique opportunity to collaborate closely with another Postdoc specializing in 3D nano image reconstruction and modelling tools development, as well as other PhDs and
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conferences, and actively participate in knowledge exchange across disciplines. As a formal qualification, you must hold a PhD degree (or equivalent). Specifically, a PhD in Materials Science and Engineering
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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hearing from researchers with oceanographic, as well as meteorological, science background. The applicant should have: A PhD in meteorology, climatology or other related fields Experience in mesoscale
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the project. Qualified candidates should have: A PhD degree in Computer Science, Electrical Engineering or equivalent. Research interests and a scientific track record in Edge Computing research fields, such as
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positive and supportive team environment. You prefer to stay organized and take pride in completing your tasks in a thoughtful and structured way. As a formal qualification, you must hold a PhD degree (or
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shared with about 400 highly skilled and motivated colleagues, with interdisciplinary backgrounds from meteorology, electrical and control engineering and data science all the way to humanities