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potential at work, learn more about our employee value proposition here (You Belong Here ). The Division of Academic and Student Affairs is the place to work for values-driven faculty and staff who
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, Physics, Electrical Engineering, Communication Engineering, or equivalents; – Knowledge in artificial intelligence, statistical and machine learning, complex systems, agent-based modeling and simulation
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices
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About the Opportunity Conduct research on machine learning, control theory, and synthetic biology. The work will combine tools from dynamical systems, control theory, and the theory of algorithms
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, design and analysis of virus-derived RNA libraries, and development of machine learning models for detecting functional elements in viral metagenomic datasets. This project is a collaboration with the
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to understand how complex biological functions emerge from interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362789/phd-learning-interactions-in-co
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, multisensory integration, or visual perception) using data analysis and machine learning techniques. Implement XR prototypes and applications to validate the developed models. Contribute to the publication
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
., Revenko, A., Teije, A. T., & Harmelen, F. V. (2023). Combining Machine Learning and Semantic Web: A Systematic Mapping Study. https://doi.org/10.1145/3586163 [2] Benoît Combemale, Pascale Vicat-Blanc
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/Anders Lien 9th September 2026 Languages English English English PhD Research Fellow in Machine Learning for Cognitive Neuroscience Apply for this job See advertisement About the position Position as PhD
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machine learning-based model to map satellite retrievals to ground based air pollutant concentrations Conducting error assessment on the derived concentration data Implementing new observational data