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of the transition from open pores to hermetically sealed fluid inclusions. To this end we have employed various small-scale imaging techniques in 2D and 3D, using facilities available in Bergen and collaborating with
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in USN’s PhD-program in Ecology within three months of accession in the position. The vacant position is part of a collaboration between the Colour Vision and Retinal Imaging Laboratory headed by Prof
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neuro-imaging (https://www.ntnu.edu/langdevlab#/view/publications ). The main responsibility of the postdoc will be to conduct research in the newly awarded ERC Synergy grant SHAPE (https://www.ntnu.edu
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for clinical AI based on patient data from heterogeneous sources notably language/speech-based sources. The activity will focus on the development of a prototype implementation of early warning- and other AI
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, computational neuroscience, experimental psychology, functional imaging, behavioral genetics, Documented experience with either psychopharmacology, laboratory testing of reward, pain, or stress in human
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reconstructions of glacier variability for selected areas in Norway. This involves landscape analyses using satellite images before field mapping. The time series will be based upon studies of sediments deposited
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learning-based image classification approaches. The objective is to quantify landscape changes over decadal timescales, with a particular emphasis on Western Norway. Relevant transformations include
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landscape analyses using satellite images before field mapping. The time series will be based upon studies of sediments deposited in glacier-fed distal lakes analysed with ultra-high-resolution scanning
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national and international partners. The PhD project will focus on integrating advanced photogrammetric techniques applied to historical aerial imagery with modern deep learning-based image classification
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measurements, biogeochemical rate modelling, high resolution 3D-imaging, isotope labelling and integrated geobiological data analysis. Analytical approaches implemented can include a multitude of advanced