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data analytics to uncover and predict patterns in large multimodal datasets [e.g. behaviour, simultaneous EEG-fMRI and eye-tracking data]. Main research themes include, but not limited to: reinforcement
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
communication skills in English Preferred Qualifications, Competencies, and Experience Research experience in multimodal learning, large language models, or reinforcement learning. Familiarity with high-performance
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, model evaluation, workflow automation, and AI-assisted orchestration of distributed learning tasks. The position will also provide opportunities to contribute to open-source software, publish research
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integrating human-in-the-loop reinforcement learning approaches. Responsible AI: Exploration of privacy-preserving AI techniques, enhancing AI safety, and addressing vulnerabilities and defenses in Large
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: At ICN2, we foster an inclusive and safe work environment, free from any form of discrimination-whether based on gender, sexual orientation, gender identity, age, origin, culture, religion, disability
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data
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methods, risk and reliability, stochastic control processes, dynamic programing, deep reinforcement learning. Strong track record in scientific contributions supported by peer-reviewed publications. Strong
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opportunities: At ICN2 we foster an inclusive and safe work environment, free from any form of discrimination-whether based on gender, sexual orientation, gender identity, age, origin, culture, religion
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IWRI - Postdoctoral Researcher in Bioinspired Circular Conversion of Multi-source Biomass Feedstocks
Job Title: IWRI - Postdoctoral researcher in Bioinspired circular conversion of multi-source biomass feedstocks for water-retentive agricultural systems Host Institute: Mohammed VI Polytechnic
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safe work environment, free from any form of discrimination-whether based on gender, sexual orientation, gender identity, age, origin, culture, religion, disability, or any other personal or social