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Field
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Archipelago, integrating it into the global e-CALLISTO network. The project will deploy new-generation spectrometers and antennas to fill the observational gap over the North Atlantic, enhancing global space
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history (PhD) - Methods and tools for data production (in-depth knowledge) - Professional environment and networks (general knowledge) - Legal and ethical framework (in-depth knowledge) - Written and oral
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), Deep Neural Networks. Probabilistic Machine Learning and Time-series Analysis. Industrial applications of AI (energy, process industry, automation). Software development experience in teams. Programming
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supported in developing cutting edge financial tools as well as their software implementation. Building up personal network: You will have the chance to meet top researchers of the field here and during
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with a high quality of life.•Integration into the research network Sensory Sciences at FAUThe Friedrich-Alexander-Universität Erlangen-Nürnberg aims to increase the proportion of wom-en in research and
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agencies. However, sharing in your network is appreciated.
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workflows between field acquisition teams, data center staff, and research collaborators to ensure seamless data transfer and integration. -Support daily operations of servers, networks, storage, and cloud
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(at least in Python and C++); ideally strong hands-on experience with ROS2. Experience in AI development, especially with neural networks. Experience with standard software development tools (Git, CI/CD, IDEs
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of Liverpool, and Prof James Chalmers at the University of Dundee. You will be sited within the vibrant research environment of the School of Biosciences but will work closely with the collaborative network
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Description Grant/funding reference: PID2022-137099NB-C42 Job title: COMMUNICATION, CODING AND PROCESSING TECHNOLOGIES FOR NEXT-GENERATION QUANTUM CLASSICAL NETWORKS (MADDIE) Research line: INFORMATION SYSTEMS