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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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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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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant
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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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networks, or network science, and relevant background knowledge n methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods. Examples
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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