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calculations or AI supported database management of high-throughput type calculations/simulations. Basic knowledge of density functional theory (DFT) is beneficial. Strong programming skills in Python
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network spanning materials science, AI, and computational imaging. Submission is possible until: 17 October 2025 Requirements Master’s degree in Computer Science, Materials Science, Physics, Mathematics
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materials. This class of materials has unique properties which make them promising candidates for next-generation electronic devices, energy storage systems, sensors, and catalysts. However, they also pose
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cent of full-time. Your qualifications You have graduated at Master’s level in Computer Science, Materials Science, Physics, Mathematics, or a related disciplines, or completed courses with a minimum of
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or comparative literature/literary studies. We also welcome interdisciplinary projects which include one or more of these specialisations. Irrespective of specialisation you will be encouraged to make use
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, particularly MIMO radar, and wave propagation channel modelling is highly desirable. We place particular emphasis on your ability to apply an interdisciplinary approach to problem-solving or your willingness
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methods to make AI systems trustworthy, verifiable, and robust against adversarial manipulations. You will have the opportunity to contribute within one or more of the following research directions
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reliable use of AI across different industries. Your work assignments You will work at the intersection of machine learning, cybersecurity, and privacy, developing methods to make AI systems trustworthy
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learning. As the communication of research results mainly takes place in English, this employment requires fluency in English, both spoken and written. Given the research potential for outreach to the public