31 density-functional-theory-dft-post PhD positions at Chalmers University of Technology in Sweden
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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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division at the department of Electrical engineering at Chalmers. Here, a team of PhD students, post-docs and senior researchers are working on modeling and numerical optimization of problems in the areas
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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 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
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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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to improve the safety of these vessels. About us The Division of Marine Technology , part of the Department of Mechanics and Maritime Sciences at Chalmers University of Technology, conducts research and
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harness the broad diversity of flavor profiles among different marine micro- and macroalgae, which ultimately depend on cultivation and post harvest processing. As a PhD-student, you will be part of
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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