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in research funding, 15 undergraduate researchers, and 9 PhD students. The successful candidate will lead the Center for Power Systems Studies (CPSS), expand industry collaborations, teach power
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exclusively by the Foundation for Science and Technology, I.P./MCTES, within the framework of the multi-year funding of R&D Units, for the period 2025-2029, through national funds (PIDDAC), aimed at the PhD in
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multilingual AI, Translation quality evaluation using AI Teach undergraduate and postgraduate courses in Computational Thinking, Machine Learning and Natural Language Processing (NLP) for translators, LLM and
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artificial intelligence, computer science, engineering, mathematics, physics, or a related discipline Demonstratable background in machine learning, information retrieval or natural language processing
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical
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/Planning Internal Number: 6832149 Part Time Lecturer - Architecture About the Opportunity The Lecturer will teach introductory courses in architectural drawing, sketching, studio design, computer modeling
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Environmental science » Earth science Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Estonia Application Deadline 31 Jan 2026 - 23:59 (Europe/Tallinn) Type of Contract
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for an FWO PhD scholarship to further develop the initiated research (if eligible). Advantages strengthening the candidate’s profile, but strictly required: Experience with machine learning or system
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 1 day ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning