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Field
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modeling in calculation processes and application of AI techniques for processing dense point clouds Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research
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computer vision models for forest-based 3D point cloud data. In recent years, large advances have been made for deep learning algorithms for high-resolution point clouds from small geographic areas. We seek
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experience. Your CV should demonstrate the scope of your work and education and indicate a good fit with the stated requirements for the position. A motivation letter (max 1 page) emphasising your specific
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the electrical contacts and magnetic field to influence the fault current interruption process. The PDRA will contribute mainly to the arc modelling part of the project and play an active role in organising and
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, signal processing and/or wireless communication. Basic knowledge of and/or experience in working with reinforcement learning/other machine learning algorithms Excellent command of spoken and written
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between the simulator and sensors located in the operating room. This will require implementing data acquisition algorithms and data processing algorithms within the simulator. The second point concerns
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | about 1 month ago
description:PhD position in cellular signaling in photosymbiosis (f/d/m) Background We invite applications for two fully funded PhD positions (3 years each) to join the newly established photosymbiosis focus group
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Are you interested in plasma physics? Do you want to help demonstrate the usefulness of radio-frequency driven plasmas for industrial processes? We are looking for a motivated PhD student to
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classification of EEG and auditory signals. The group of the project is multidisciplinary, with experts in signal processing, machine learning, acoustics and language. The successful applicant will perform
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integrate multiple signals during communication (e.g., using insights from psycholinguistics and neuroscience to inform computational models of multimodal language processing- Building AI agents that engage