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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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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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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
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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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(CFD), including chemical reaction models, but could also involve other modeling methods such as Density Functional Theory (DFT) or kinetic Monte Carlo. Your qualifications You have graduated at Master’s
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application! We are looking for a PhD student in theoretical physics with a focus on the theory of magnetic materials. Your work assignments Your tasks will be to carry out research using advanced theoretical