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interconnects for next-generation AI compute clusters. Information The smart optical networks lab (SONL) at the Electro-Optics Communication (ECO) group at Eindhoven University of Technology is recruiting for a
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Computer Science, Data Analysis, Software Engineering, Physics, Mathematics or related disciplines with a strong academic record. Strong programming skills, preferably in Python, and experience developing non
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headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here
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. Enforcing these is hard when the data, the model, and the rules belong to different parties, none of whom can hand over what they hold. Privacy-preserving AI protects data and models but not rules, while
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of Computing Science values gender diversity, and therefore particularly encourages women and those outside the gender binary to apply for the position. For additional information, please contact Asst. Prof
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of "America's Best-In-State Employers" for 2025. Location Statesboro Campus - Statesboro, GA Department Information Computer Science Job Summary The Student Assistant will support the Department
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16 Aug 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Materials engineering Engineering » Mechanical engineering Researcher Profile
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University of Girona (UdG) - Institute of Computational Chemistry and Catalysis (IQCC) | Spain | 3 months ago
15 Jul 2026 Job Information Organisation/Company University of Girona (UdG) - Institute of Computational Chemistry and Catalysis (IQCC) Department Chemistry Research Field Chemistry » Computational
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The continuous release of Earth Observation (satellite) data and the emergence of Machine Learning methods open up new possibilities for understanding forests. These large datasets provide
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Are you fascinated by scientific and technological innovations in mechano-driven cartilage tissue engineering? Are you driven to develop novel in silico frameworks that deepen mechanistic