32 postdoctoral-density-functional-theory PhD positions at Chalmers University of Technology
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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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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Join us for a fully funded PhD position in theoretical machine learning to uncover how and why transformers work. Explore their inner mechanisms using information theory. As part of this project
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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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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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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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funded by a EU programme Reference Number 304--1-13797 Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to be a part of the on-going revolution in
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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
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to operate around the clock. By ensuring the performance, longevity, and circularity of industrial systems such as advanced manufacturing (e.g., automotive and battery) and renewable energy (e.g., energy
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these systems operate in, ACPS increasingly rely on data-driven learning-enabled components to perform a variety of challenging decision-making tasks. While indispensable for autonomy, learning-enabled components