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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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focusing on: Quantum mechanical calculations using density functional theory. Mean-field modeling and Monte Carlo simulations for reaction kinetics. Theoretical spectroscopy By combining quantum mechanical
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laboratory work and data analysis? Then this position may be right for you. While the focus will be on your research and personal development as a researcher, the position also provides opportunities
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. You enjoy combining experimental laboratory work with theoretical analysis and modelling. While your main focus will be the research project and your own development as a researcher, the position also
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This PhD position offers a unique opportunity to advance safe and transparent control for autonomous, over-actuated electric vehicles. You will work at the intersection of model predictive control
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spaces of AI models will be analyzed in their facts using quantitative methods from data science and AI, results of which then be investigated using qualitative methods and theory of critical studies
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behavior of programs at a high level. Automata theory — to manipulate logical formulas and domain representations. Two-player games — to reason about strategies and synthesized programs. The work involves
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
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of waveforms for satellite communication and radar systems communication/radar system performance analysis using theory and simulation field tests in relevant operating conditions retrieval of geophysical
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influencing equality, but we see a need for research that aims at understanding the role of other actors and factors in this arena. The goal is to understand how the problem of equal participation in STEM is