13 machine-learning-engineer PhD positions at Chalmers University of Technology in Sweden
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the Swedish National Infrastructure for Computing (SNIC) and the Chalmers Centre for Computational Science and Engineering (C3SE). Learn more about the project and the research: Project overview Due
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
performance in core mathematics and machine learning courses Master’s degree (or near completion) corresponding to at least 240 higher education credits in mathematics, computer science, electrical engineering
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Merits: Experience with Matlab Prior coursework or project experience in railway mechanics Background in signal processing Knowledge of machine learning techniques Main responsibilities Your primary
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corresponding to at least 240 higher education credits in electrical engineering, engineering physics, biomedical engineering, or related disciplines. Very good knowledge of signal processing, machine learning
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Chalmers' new research initiative Ocean is seeking a highly motivated PhD student in environmental analytical chemistry and machine learning. In this role, you will work with high-frequency
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on the hypothesis that the future of building design lies at the intersection of physically sound building simulation models and machine learning (ML) techniques. Key considerations include effectively integrating ML
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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum
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dynamics simulation and controls toolbox fascinating? The research of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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progression, machine learning. You will collaborate locally and internationally with groups in both theory and experiment. You will disseminate your findings by publishing in scientific journals and presenting