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between predictive performance, computational efficiency and scalability, using high-performance and cloud computing environments. Depending on the agreed research direction, you may also explore hybrid
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are still present. This PhD research aims to develop new and efficient AI-based solutions for processing LiDAR data (2D/raster and 3D/point clouds) and improve the detection of sub-canopy archaeological
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monitoring 96 parallel cell-culture experiments under precisely controlled environmental conditions. The system integrates robotics, automated sample handling, sensor networks, imaging systems, cloud computing
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PhD Scholarship Two projects are available to analyse observations of water world candidates made with the James Webb Space Telescope, and to develop climate simulations to explore atmospheric
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4th October 2026 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Digital Sovereignty Apply for this job See advertisement This is NTNU NTNU
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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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Change Adaptation (CCA) simulations and activities in urban environments. The PhD project should leverage multi-scale geospatial data (remote sensing/aerial imagery, point clouds, maps, etc.) and GeoAI
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a strong background in artificial intelligence and 3D computer vision, with solid programming skills and an interest in 3D data processing (e.g. point clouds and neural scene representations), along
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training: Enroll in the VISESS doctoral school , with benefits described here: https://visess.univie.ac.at/phd-programme/ . Benefit also from the offer of soft skills training, coaching, and professional
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on high-performance computers Research freedom: Develop your own ideas within the project’s broad scope. Inspiring and supportive working atmosphere: Join an interdisciplinary team of 4 PhD students