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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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of robots to interact with the surrounding environment and humans during the execution of specific tasks. Project description The vision of RAI is aiming in closing the gap from theory to real life, while
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of robots to interact with the surrounding environment and humans during the execution of specific tasks. Project description The vision of RAI is aiming in closing the gap from theory to real life, while
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the intersection of control theory, robotics, artificial intelligence, and signal processing, and is a key enabler of future intelligent infrastructure.This project will focus on the development of novel control
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Engineering and Autonomous Systems division . We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and learning
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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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media and artificial intelligence, are transforming the conditions for political communication, mobilisation, and t power in contemporary societies. The project should be grounded in sociological theory
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Bachelor, Master and Doctoral levels, as well as a thriving research environment and many opportunities for personal development. Our mission is to advance the theory and practice of business, with specific
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supervised by Sebastian Throm. The subject area of the announced position covers kinetic theory, non-local diffusion and dynamics on graphs. The precise research direction will be determined together
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specific focus on Aerial and Space robotics. The vision of RAI is aiming in closing the gap from theory to real life, while the team has a strong expertise in field robotics. Specific application areas