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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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CLOUD and HALO COTANGO. Doctoral training and participation in international conferences are part of the programme. How to apply Please send your application as a single PDF file (letter of motivation, CV
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automatic interpretation of measurement data. A cornerstone of our systems is the automated, AI-driven interpretation of 3D point cloud data, which requires high-quality training datasets and, ideally, model
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of HPC or cloud computing. Practical experience with computer vision. Experience with databases, research data management, GIS or geospatial data processing. What we offer An opportunity to play an active
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December 2032. About Us The ML Cloud team designs, runs and safeguards high-performance computing infrastructure tailored to machine learning workloads. Our state of the art systems are distributed across
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Future. Discover. Together. The Computer Vision & Graphics group of the Vision & Imaging Technologies (VIT) department is looking for a student assistant in the area of deep learning for scene
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high-performance computing (HPC) environments and/or cloud-based data processing infrastructures Familiarity with workflow management systems (e. g. Nextflow) and workflow orchestration Experience with
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modeling and programming for model optimization and machine-learning applications Perform material characterization of various optical glass materials What you contribute Currently studying Computational
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Call for applications for disciplines such as: electrical engineering, computer science, control systems, or related fields. In the "Navigation mobile Robots" research group, we develop autonomous
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EGI- and EOSC-aligned environments. Your tasks include Designing and developing containerized architectures optimized for EOSC cloud environments Building and operating high-performance compute