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Job Description Do you want to work on real-world challenges at the intersection of machine learning and power system stability? We are looking for a PhD student with a background in control
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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, machine learning tools, and simulation techniques. If you thrive at the intersection of engineering, data, and advanced computational science, this position will allow you to contribute meaningfully
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(supervised by Assoc. Prof. Ivana Konvalinka) and machine learning researchers (co-supervised by Prof. Lars Kai Hansen), you will be responsible for designing and running interactive multi-person (hyperscanning
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mathematics, or a related field. The candidates for the PhD position will be assessed on the following criteria: Strong skills in probabilistic modelling, machine learning, or simulation techniques. Programming
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, or a related field. Have documented experience in some of the following: Computational materials modelling or quantum mechanical simulations (e.g. DFT, MD). Machine learning / deep learning (preferably