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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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- ; Xi'an Jiaotong - Liverpool University
- Fudan University
- Harbin Engineering University
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- Hong Kong University of Science and Technology(Guangzhou)
- Prof. Ruilin Pei and Shenyang University of Technology
- The Hong Kong University of Science and Technology (Guangzhou)
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, China [map ] Subject Areas: Computational Mathematics, Applied Mathematics, Artificial Intelligence, Numerical Analysis, Optimization, Statistics Appl Deadline: none (posted 2024/08/02) Position
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Algebra, Algebraic Geometry, Number Theory, Mathematical Optimization Cryptography: Post-Quantum Cryptography, Multi-Party Computation, Zero-Knowledge Proofs, Fully Homomorphic Encryption, Privacy
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/academics/four-hubs/society-hub/financial-technology . We seek talents in the cutting-edge research in FinTech. Applicants must have PhD degrees in FinTech or related fields, e.g., Computational Mathematics
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reactors; Experience with chemical process optimization and industrial collaboration is an advantage; Excellent analytical skills and the ability to handle complex datasets; PhD Graduation within 3 years
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drug development, gene/cell therapy, clinical pharmacy, and new vaccine development. The Academy plans to offer undergraduate, Master’s and PhD degree programmes in Applied Statistics (Biostatistics
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to, Dynamical Systems, Bifurcation Analysis, Complex Networks, Optimization, Mathematical Biology, Biostatistics, Mathematical Epidemiology, Computational Biology, Bioinformatics, P robability Theory, Stochastic
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for distinguished professorship. Candidates in areas including, but not limited to, Dynamical Systems, Partial Differential Equations, Optimization, Stochastic Differential Equations, Stochastic Partial Differential
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interaction and integration; Continuously developing new products with the emerging customers’ needs in mind; Collaborating with other units of the department to optimize resources and contribute to the overall
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, treatment planning, and patient care. The research will involve data collection and preprocessing, model architecture design, pre-training and fine-tuning, evaluation and benchmarking, and model optimization
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, separation, and catalysis, with a focus on carbon capture and conversion technologies. Artificial Intelligence: Leveraging AI and machine learning to optimize material design and catalysis processes. Carbon