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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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with silicon probes, Neuropixels, tetrodes or in vivo imaging. Demonstrated experience with computational, statistical analysis or modeling of large-scale behavioral and/or neurophysiological data (in
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results. You will join the Section for renewable energy and forest sciences and conduct cutting‑edge research using remotely sensed point‑cloud and image data to map forests. The position is part of two
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and Transmission Electron Microscopy studies at the Department of Physics. This PhD position is within the field of experimental materials physics and nanotechnology, in the project «Nanoscale imaging
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position is within the field of experimental materials physics and nanotechnology, in the project «Nanoscale imaging of magnetic skyrmion dynamics in thin film devices» (NIMSKY). Magnetic skyrmions
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“Female Heart”. The researcher position has a temporary financing for two (2) years from 01.11.25. About the project/work tasks: Advanced image analysis of ultrasound images Statistical analysis
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(imaging, 3D point clouds, or multispectral data). Good presentation skills, written and oral in English Qualifications considered an advantage Background in plant genetics/genomics/phenomics (SNP analysis
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neuropsychology. Methods for brain-imaging and brain stimulation are employed to understand, predict, and change human behaviour. Further, basic human neuroscience approaches are translated to study and improve
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characterize forest structure. Remote sensing data, such as images, lidar, and photogrammetric point clouds acquired from drones, aircraft, and satellites, will play a central role in the development
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performed in close collaboration with experienced team members. Additionally, the candidate will acquire skills in performing in vivo PET/SPECT and MR/CT imaging experiments and data analysis. The candidate