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climate change - Computer vision, e.g., colour vision, human colour vision, colour appearance models, etc. - AI technology, e.g. statistical learning, neural network learning, deep and transfer learning
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climate change - Computer vision, e.g., colour vision, human colour vision, colour appearance models, etc. - AI technology, e.g. statistical learning, neural network learning, deep and transfer learning
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Torbein Kvil Gamst 1st February 2026 Languages English English English Faculty of Science and Technology PhD Fellow in Computer Science Apply for this job See advertisement The position An exciting
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integrated circuits (PIC). An optical set-up will be used to characterize the chips and demonstrate the capabilities of the PICs. The PhD will collaborate with researchers in machine learning for analysis
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: Develop and apply new machine learning and computer vision methods such as large-language models and vision-language models for high-throughput analysis of video data. For NeuroAI focus: Apply data-driven
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duties as assigned. REQUIREMENTS: REQUIRED: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong programming skills. Strong background in machine
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investigators to acquire essential academic credentials and research skills with the purpose of increasing competitiveness for MD, PhD, or MD-PhD programs in biomedical sciences. Primary Responsibilities Devote
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of the Department. The research activities of the department fall under eight broad headings, though there is much overlap in practice: Information Engineering (Robotics, Computer Vision and Machine Learning
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Pose EstimationStrong background in computer vision and machine learning applied to pose estimation and visual servoing; Experience with OpenCV, PCL (Point Cloud Library), PyTorch/TensorFlow, and 3D
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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