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modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department
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knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics
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on challenges related to computer vision for geophysical image data. You will investigate and develop robust methods for training models, exploring/developing approaches for multimodal data, utilize context
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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to both contribute to new advances in a field with real world applications. Your research focus will be on challenges related to computer vision for geophysical image data. You will investigate and develop
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to both contribute to new advances in a field with real world applications. Your research focus will be on challenges related to computer vision for geophysical image data. You will investigate and develop
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generation of scholars and research leaders in this increasingly important field. By fostering collaborative research across linguistic theories, neuroscience, and language acquisition/processing, we will
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at the Department of Informatics. Position as Postdoctoral Research Fellow available at the Department for Informatics with the research group Digital Signal Processing and Image Analysis (https://www.mn.uio.no/ifi
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employees and 43,000 students work to create knowledge for a better world. You can find more information about working at NTNU and the application process here . About the position We are offering an exciting
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(time-course and quantity of gaze/eye-movements), neuro-physiology of language processing in the brain and neuro-imaging (https://www.ntnu.edu/langdevlab#/view/publications ). The main responsibility