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more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be
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and computational physics High-energy physics/astrophysics/cosmology Statistical mechanics/complex systems/non-linear physics Machine learning/first-principles calculations/large-scale simulations
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project The main objective of this PhD project is to explore and analyze bio-inspired neural architectures for early detection from spatio-temporal data under realistic sensing and computational constraints
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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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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, artificial intelligence—and particularly machine learning methods—has become indispensable. Depending on the specialty, processed data may include numerical values, point clouds, text or images, often
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doctoral students. We conduct world-leading research and education in both theoretical and experimental physics, including the development and use of large-scale infrastructures. We also collaborate
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of areas, including AI and machine learning, cloud and mobile computing, computer system and information security, evolutionary computation, computer vision and graphics, and bioinformatics
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or industry equivalent work at a computing facility, or using/managing HPC resources Experience working with large scale machine learning models Experience with performance optimization, debugging, and
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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation