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Field
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strategy, the processing of sensor data (laserscans, images, pressure, etc.), as well as the reactive control of robotic arms. In order to apply for this position, the candidate should possess in-depth
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are geared to people's needs: Health, Safety, Communication, Mobility, Energy and Environment. We are creative, we shape technology, we design products, we improve processes, we open up new paths. Interested
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advanced attosecond technology to track and control electron dynamics in matter. Our approach enables real-time observation of electronic processes and manipulation of properties at the atomic scale
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The »High-Performance Cutting « department develops technologies and application-oriented solutions for cutting along the entire process chain - from process design and pre-process simulation
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EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites | Darmstadt, Hessen | Germany | 3 days ago
9 Dec 2025 Job Information Organisation/Company EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites Research Field Computer science Environmental science Engineering
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hierarchically organised samples. To achieve this, we need to improve our understanding of the physical image formation and data recovery processes, among other topics. The advertised positions will focus
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, hydrogen and electricity. Be part of change Diverse and varied activities in the context of project management and coordination in the fields of bioenergy, combustion technology and CO2-neutral process heat
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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) systems and specific scientific communities. It aims to optimize not only management of data transfer, processing and storage but also computational analysis, visualization and public availability, thereby
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engineering, or a related field Strong expertise in computer vision with a focus on modern 3D reconstruction techniques Extensive experience with PyTorch: confident training of machine learning models on single