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of expertise in fundamental research on condensed matter, ranging from topics such as Quantum Materials / Electronic Structure & Quantum Many-Body Theory / Nanoscience / Solid State Spectroscopy / Solid State
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a similar field; Strong mathematical background: basic knowledge of graph theory and excellent background in linear algebra, finite fields and rings; Strong background in digital hardware design and
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that enable interpretable models to learn from deep representations. In this project, the researcher will develop theory and algorithms for (hybrid) model selection that allows to exploit domain knowledge
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, or a similar field; Strong mathematical background: basic knowledge of graph theory and excellent background in linear algebra, finite fields and rings; Strong background in digital hardware design and
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teaching and research around a variety of thematic, geographical and theoretical approaches including, among others, network theories, connected history, reading history, medical humanities, material culture
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project (thesis, paper, etc.) Analytical mindset: You have a passion for solving complex problems and a solid foundation in math/stats/ML theory Teamwork and Communication: You enjoy interdisciplinary
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projects under senior supervision (2) Exchanging knowledge with the scientific community and the general public (3) Network-wide training in theory and methods (4) Complementary training courses (5
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of complexity theory, systems thinking, and simulation modeling. • Stakeholder management, marketing strategies, and customer satisfaction modeling. • Both basic and applied research, including contract research
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Research focusses on theories and models from marketing and consumer research that can contribute to successful new product development (NPD). The group has experience in teaching and conducting high quality
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open-source code (Python) that is high-performing and scalable to comprehensively quantify uncertainties using probability theory. This is where you will contribute: in the application of the developed