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profile for their ideal candidates are described as follows. PREMAL is a project focused on privacy-preserving machine learning using FHE. The project will investigate trade-offs between accuracy, time, and
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and research, in and outside academia. The position will specifically focus on Reinforcement Learning for Resource-Constrained Project Scheduling Problem (RCPSP). The Ph.D. candidate will be a member of
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Teaching and supporting of learning activities in courses related to networking Contribute to career-development activities that support your progress as an independent researcher Be prepared for changes
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the Section for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and
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the researchers from Department of Automation and Process Engineering will play a key role. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early
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: OUH - Cell and tissue dynamics (Bøe) Project description GENESIS is a newly established Life Science Convergence Environment that brings active matter physics, cell biology, and machine learning
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intelligence, data analytics, uncertainty analysis, probabilistic modelling, or statistical learning you have experience working on relevant research or project activities involving machine learning or data
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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resilience of bridges under climate change-induced hazards such as flooding, scour, and debris impacts. The research aims to develop advanced numerical models and machine learning tools to predict loads
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of Visual Intelligence is to develop novel, innovative solutions based on deep learning to extract knowledge from complex image data. Deep learning, aided by machine learning techniques in general, has led