223 computer-programmer-"https:"-"CNR" "https:" "https:" "https:" "https:" "University of Innsbruck" Fellowship positions at Nanyang Technological University
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approaches, share datasets, and integrate results into broader fusion research programmes Job Requirements: PhD degree in physics Demonstrated experience in scientific computing, including programming
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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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The NTU AI-for-X Postdoctoral Fellowship (AI4X-PDF), jointly supported by Nanyang Technological University (NTU) and Singapore’s National Research Foundation (NRF), is a prestigious programme
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well as large-scale GPU computing facilities for deep learning. Our Lab aims to hire a Research Fellow to lead a research project on Real-World Deepfake Detection and Image Forgery Localization. The role will
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mathematical modeling framework to find the optimal operation strategy for public transport services with autonomous vehicles Conduct computer programming to verify the efficiency of the designed solution
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: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering, or equivalent. Independent, highly analytical, proactive, and a team player; strong verbal and written communication skills
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responsible for: Supporting empirical research projects in investments and financial markets, with a strong emphasis on computational and AI-based methods. Designing, implementing, and maintaining research
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PhD qualification degree in Electronic Engineering or Computer Science Familiarity with pinching antennas and machine learning Good written and oral communication skills Proficiency in python
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academia, industry, and national laboratories Job Requirements: PhD in Materials Science, Chemistry, Physics, Computer Science, or a closely related discipline. Strong experience with Density Functional
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and PhD students on computational mathematics and AI methodologies. Job Requirements: A PhD degree in Applied Mathematics, Computer Science, Engineering, or a related quantitative field. Deep expertise