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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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methods with the ability to implement and evaluate machine-learning systems at scale. Candidates may come from topological data analysis, geometric deep learning, network science, statistical physics
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-driven approach for optimizing the growth of semiconductor materials by combining machine learning with a physics-based understanding of the growth process. Doping and processing of ultra-wide bandgap
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We work on highly topical, socially relevant issues and offer you the opportunity to actively shape change! You can expect a wide range of opportunities: Meaningful tasks: The opportunity to conduct exciting research in an international and multidisciplinary environment with outstanding...
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the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy to consider candidates in one of the two fields who can demonstrate a strong basis for working in this cross
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project focused on developing an advanced machine learning framework for spatio-temporal datasets. The position is for 2.5 years and is partially funded by the Dutch Research Council (NWO) through
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Associate position focusing on control systems engineering, artificial intelligence (AI), and scientific machine learning (SciML) applied to nuclear fusion energy. The successful candidate will join the
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of thousands of molecules in our fully automated high biosafety screening facility CAPS-IT against multiple viruses. You will be responsible for the development and deployment of advanced machine learning models
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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established lasting ties with industrial partners and created several spin-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona