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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We have a vacancy for a PhD candidate in machine learning
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31 Aug 2026 Job Information Organisation/Company Fondazione Bruno Kessler Research Field Other Researcher Profile Other Profession Positions PhD Positions Application Deadline 24 Sep 2026 - 23:59
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checks with advanced machine learning architectures, specifically Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAEs). The researcher will use historical QC archives dating back
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
or equivalent experience in machine learning or a related quantitative field (Computer Science, Artificial Intelligence, Statistics, Mathematics, Physics, Computational Biology/Chemistry). Candidates will be
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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, machine learning or neuronal population analyses would be an advantage. Specific Requirements We are looking for a candidate with a strong interest in scientific software development and quantitative
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This is an EU funded project, named QUESTING, with project number 101227218, within program HE / MSCA. See also https://questing-project.eu/2025/12/16/call-for-applications-15-fully-funded-phd-positions/
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warmer and wetter world. RAPTURE brings together high resolution physical simulations, machine-learning climate emulators, and new perspectives on the dynamics of weather and climate to understand i) what
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is