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Field
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-impact projects across our core focus areas. We are looking for curious minds who are excited to push the boundaries of responsible AI. Learn more about the lab's work at: https
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wide-field surveys (ZTF, LSST, Argus). • Develop algorithms for low-latency multi-messenger searches combining gravitational-wave, gamma-ray-burst, fast-radio-burst, and optical detections. • Make
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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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of course offerings, musical ensembles, and dance companies with a national reputation that attracts students from across the campus. More information about the department can be found at https
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
. Nutrition for Precision Health, powered by the All of Us Research Program is a new initiative to develop algorithms that predict individual responses to food and dietary patterns. The NPH Consortium consists
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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
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engagement, online communities, influencers and creators, digital advertising and public relations, algorithms and platforms, artificial intelligence and media, misinformation, or the social and cultural
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and FCT code. 2023.18225.ICDT and e DOI https://doi.org/10.54499/2023.18255.ICDT , funded by COMPETE 2030 by Portugal 2030, and by the European Union financial support from national funds/OE through