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: Remote participation in the war in Sudan Start date of both positions: 1st of October 2026. via Unsplash Research for a just and equal world CMI's vision is to generate research for a just and equal world
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equivalent. Strong background in machine learning and computer vision. Prior experience in data-efficient classification, synthesis, and detection is preferable. Strong publication records in top-tier machine
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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15th December 2025 Languages English English English The Department of Computer Science has a vacancy for a Postdoctoral Fellow in AI Enhancement of Game-based Learning Apply for this job See
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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from additional data such as wireline logs or well reports. You are suited for this position if you are highly motivated, have interests in computer vision and neural networks, and want to both
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aquaculture (e.g., behavioral analysis, growth prediction, digital twin, computer vision.) Develop, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets
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of these publications and your part in these. Selection Criteria: Essential PhD in Computer Science, Informatics, Data Science, Statistics, or a closely related area. Substantial research experience in applied Artificial
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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the Integreat community whose members are in Tromsø and Oslo. Your role as a PhD Fellow You will be an integral part of Integreat via the UiT Machine Learning Group. You will engage in collaborative research with