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Employer
- European University Institute
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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- Beijing Academy of Quantum Information Sciences
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Field
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. Possible research topics include: Scientific machine learning Numerical partial differential equations (PDEs) Computational fluid dynamics Neural operators High-performance computing Data-driven
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Skills: • Prior experience in quantum information, quantum computing, machine learning. • Proficiency in computer programming matlab, python, mathematica. How to Apply and required documents: • Personal CV
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are especially encouraged: (1) statistical mechanics, condensed-matter theory, quantum field theory; (2) tensor networks, quantum information, quantum algorithms; (3) machine learning, generative models, large
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Equations & Applications Data Science, Machine Learning, and AI Mathematical Materials Science and other emerging fields in applied mathematics Qualifications: A PhD (completed or expected by the date
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innovation in autonomous scientific discovery. • Science of AI: We investigate the theoretical foundations of machine learning itself, leveraging tools from quantum information, statistical mechanics, and
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physics, nuclear astrophysics, quantum sensing, machine learning, gravitational waves, and particle theory and experiment. Faculty members include Professors Weiping Liu, Jie Chen, Sebastian Garcia-Saenz
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of China and international passport holders. XJTLU offers our undergraduates and postgraduates over 100 programmes with a diverse spectrum of courses. With a focus on innovative learning and teaching, and
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Position Description PART 01 Introduction of the project group Relying on mathematics, quantum computing, computer, microelectronics and other disciplines, Center for Network and Information
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have no obligation to teach, but will be required to apply for an external funding from National Natural Science Foundation of China and some other sources. The main obligation of a successful candidate
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) Start date: January 2025 or later Requirements 1) Have obtained or about to obtain a Ph.D. degree in Mathematics. 2) Excellent previous research record. 3) Proven ability to learn relatively fast advanced