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Field
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physics or theoretical chemistry, with interest in electronic-structure theory and method development. Experience in computer simulations and programming is advantageous. Very good communication and writing
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interdisciplinary doctoral program starting July 2026. 🔬 What we offer Join a highly collaborative, DFG-funded research environment that brings together experts from physics, chemistry, biology, and materials
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individuals holding a Master of Science degree in condensed matter physics or materials science, with a focus on numerical simulations - Prior experience with theoretical and or computational project work is
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conferences Your profile - Master?s degree in physics, mathematics, computer science, or a related field - strong analytical skills and solid theoretical background - experience in machine/?deep learning and
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international journals and conferences Your profile Master’s degree in physics, mathematics, computer science, or a related field strong analytical skills and solid theoretical background experience in machine
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information-theoretic approach that embeds security directly into the physical transmission layer, ensuring resilience against future attack methods, e.g., by quantum computers. We are seeking a highly
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language. Programme duration 6 semesters Beginning Winter and summer semester Application deadline Varies, please check our website Tuition fees per semester in EUR None Combined Master's degree / PhD
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Max Planck Institute for the Physics of Complex Systems • | Dresden, Sachsen | Germany | about 20 hours ago
dynamical manipulation of quantum systems. However, the scope of the graduate school extends to various related topics in theoretical and computational chemistry and both theoretical and experimental
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/PhD programme, with the first year consisting of theoretical and practical training in lectures, tutorials, practical courses, laboratory rotations, and seminars. After the first year, the majority
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master’s degree in mathematics, theoretical computer science, machine learning, or a closely related field. Strong background in discrete optimization, algorithms, or reinforcement learning. Good programming