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Lawrence Berkeley National Laboratory is hiring a Postdoctoral Researcher – Machine Learning for Materials Science within the Molecular Foundry division. Molecular Foundry is a Department of Energy
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machine learning, deep learning, audio/image/video classification, attention mechanisms, zero/few shot learning, and evolutionary algorithms. The Research Associate should have proficient programming skills
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and economy that respect people and their environment. We are looking for our next postdoctoral researcher in computer graphics and machine learning to join the Image, Data and Signal (IDS) department
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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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criteria We seek a researcher with strong machine learning modelling expertise with experience in the analysis of challenging large-scale data sets. Experience with cellular imaging data or virology
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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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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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-disciplinary domain. Specific research topics to apply to bioacoustics might include: low-footprint machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods
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machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods; representation learning; analysing sound sequences and vocal interactions; category discovery; Perma
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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