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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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train connections to the North Sea coast, Hamburg, Berlin, the Netherlands, and Denmark. PhD Program: Research component The focus of the PhD Program and of each individual PhD thesis is on the research
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well as candidates with a background in machine learning methods. The PhD programme will straddle the boundaries between the field of wave modelling and the general field of machine learning, and we will set up a team
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University. Requirements A master’s degree in (applied) mathematics (or related), with a strong background in computational methods, preferably also using computational frameworks for machine learning in
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for: PhD Candidate, Reinforcement Learning for Sustainable Energy This position is embedded
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UC Berkeley after obtaining her PhD from the University of Amsterdam for which she did research at MIT and Sigma Computing. Her general research interest is on the intersection of machine learning
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of Amsterdam. Interested in developing fundamental machine learning techniques for tabular data to democratize insights from high-value structured data? Then this fully-funded 4-year PhD position starting Fall
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, business school scientists, system modeling and optimization researchers, computer scientists, legal experts and social scientists working on energy topics. Description of the PhD project The project
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Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
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adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric