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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 2 days ago
job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Experimental studies on the safety
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for large-scale and distributed systems. The role focuses on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position
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and real-time data acquisition systems. Participate in testing and deployment of UAV demonstrators at UM6P and OCP sites. Methodology: AI Development: Reinforcement learning, computer vision, and sensor
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is to provide talent, services, and technology that empower SUNY to research, innovate, and transfer discoveries that transform the world's knowledge economy. Our vision is to make SUNY the best place
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is to provide talent, services, and technology that empower SUNY to research, innovate, and transfer discoveries that transform the world's knowledge economy. Our vision is to make SUNY the best place
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programming skills Preferred Qualifications Track record of top-tier machine learning publications Experience with machine learning on medical images Experience designing language model or vision–language model
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benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Contribute your computer vision
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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 4 days ago
job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Preclinical research
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a particular emphasis on error-corrected methods for future fault-tolerant quantum computing. The algorithms will be designed to address key models of quantum materials, such as the Hubbard model