Sort by
Refine Your Search
-
Language Models Time-Series Data Prediction and Modeling Intelligent Decision-Making and Optimization Algorithms Strong programming skills (proficient in Python, PyTorch/TensorFlow, etc.). Strong
-
of Large Language Models Time-Series Data Prediction and Modeling Intelligent Decision-Making and Optimization Algorithms Strong programming skills (proficient in Python, PyTorch/TensorFlow, etc.). Strong
-
, energy) or discrete manufacturing (e.g., electronics assembly, automotive, home appliances). Explore the integration of large language models and reinforcement learning for real-time optimization, fault
-
(QMC), density-matrix renormalization group (DMRG), etc. The applicant should be able to write and implement numerical codes; good command of at least one programming language and basic Linux experience
-
collisions at the LHC (ATLAS) and prospective future colliders (CEPC/SppC); and related theoretical efforts. The division has an active visitor program and co-organizes several conferences and workshops
-
written and verbal communication skills in English. 4. Preference will be given to candidates experienced in using Sage, PARI/GP or Magma to do number theoretic computations (L-functions, modular forms, etc
-
, education allowance, relocation support etc. Adequate research funds, and university’s supports to apply for national, provincial and municipal talent programs. Requirements: Ph.D. in Mathematics
-
of Intelligent Computing and MoE Key Lab. Additional funding available for recipients of prestigious fellowships: Postdoctoral Innovative Talents Support Program Postdoctoral International Exchange Program
-
theoretical physics specializing in theoretical condensed matter physics, quantum optics or mathematical physics. Excellent analytical capability is absolutely necessary and programming skills are wished for. A
-
countries, including EPSRC Programme grant "Symmetries and Correspondence". The principal investigator is Professor Ivan Fesenko. Professor Ivan Fesenko's Higher Number Theory page: https://ivanfesenko.org