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Migration has long been central to political contestation, but digital platforms have transformed how it is discussed. Online debates do not revolve around facts alone. They unfold through rapidly circulating narratives that combine language, images, personal stories, and emotional appeals. Such...
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the Faculty of Electrical Engineering, Mathematics, and Computer Science (EEMCS). MS3 specializes in research and education at the cutting edge of microwave systems, focusing on both fundamental and applied
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of service. The project is conducted in collaboration with two clusters at the Department of Mathematics and Computer Science of TU/e: Data and Artificial intelligence . Novel learning algorithms will
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knowledge, innovations, and solutions that help move the world forward. Faculty of Electrical Engineering, Mathematics and Computer Science The Faculty of Electrical Engineering, Mathematics and Computer
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Engineering, Mathematics and Computer Science The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other
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) in computer science, artificial intelligence, data science, applied mathematics, physics, electrical engineering, or a related field. You have a solid background in machine learning; experience with
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departments to make a fundamental connection with: Biology, Chemistry, Information and Computing Sciences, Mathematics, Pharmaceutical Sciences, and Physics. Each of these is made up of distinct institutes
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, such that we can model systems consisting of a wide range of varying materials. These extensions will be employed and tested on actual measurement data as a benchmark. The project will involve mathematical
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variety of perspectives and backgrounds. The Faculty has six departments: Biology, Pharmaceutical Sciences, Information & Computing Sciences, Physics, Chemistry and Mathematics. Together, we work
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is decentralized or only partially observable? Depending on the research direction, you may employ techniques from mathematical modelling, machine learning, uncertainty quantification, distributed