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Field
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satellite constellations [2]. This PhD aims to develop a comprehensive analytical and algorithmic framework for deterministic QoS guarantees in dynamic LEO satellite constellations. The research will pursue
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campus. We are particularly interested in researchers working in mathematical artificial intelligence, broadly construed. This includes, but is not limited to: machine learning algorithms, formal proof
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data) will help validate observations and refine predictive models. Automated monitoring tools (scripts, dashboards, alerts) incorporating machine learning algorithms or statistical methods will be
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error-correcting codes, establishing fundamental performance limits, and building practical decoding algorithms and architectures. Your research will sit at the interface between the classical and quantum
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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Researcher position. The selected candidate will work on research and development for testing, analysis, and integration of AI and machine learning (ML) algorithms in new simulation and training architectures
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involving Prof. Dr. Michael Bader (TUM CIT, Hardware-aware algorithms for HPC) , Prof. Dr. Felix Dietrich (TUM CIT, Physics-enhanced Machine Learning) , and Prof. Dr. Hartwig Anzt (TUM CIT, Computational
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Ref. 4364_All. 3 - Methods and Tools for Secure and Autonomous Brain-Inspired Cyber-Physical Systems
. The neuromorphic component will address the design, optimization and deployment of Spiking Neural Networks (SNNs) and event-based algorithms on embedded processors and specialized accelerators, including data from
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is available at https://colalab.ai/ . At EI, the group will develop an ambitious Generative Digital Biology (GDB) programme, developing multimodal, cross-organism and experimentally grounded AI systems
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is available at https://colalab.ai/ . At EI, the group will develop an ambitious Generative Digital Biology (GDB) programme, developing multimodal, cross-organism and experimentally grounded AI systems