Applications are invited for PhD students in quantum computing and artificial intelligence, under the supervision of Assistant Professor Yuxuan Zhang at the National University of Singapore, starting in August 2027. At least three fully funded places are available, in the School of Computing and in the Department of Physics.
The group works at the interface of quantum information, quantum many-body physics and machine learning: on when quantum computers can outperform classical ones and how to verify that they have, on using them to simulate quantum matter, and on bringing machine learning to bear on both. Projects can be theory-leaning, numerics-leaning or hardware-facing, and students will have opportunities to work with industry partners in quantum computing and with collaborators across North America, Europe and Asia. Joining a group in its first years means close supervision and substantial ownership of your project.
Singapore is expanding rapidly in quantum: the National Quantum Strategy commits about S$300 million over five years, the Centre for Quantum Technologies at NUS is becoming a national R&D centre, and Quantinuum has opened an R&D centre in the city.
To apply, submit an application to the PhD programme at NUS, naming "Zhang, Yuxuan" as your proposed supervisor. Note that the two departments have different deadlines for the August 2027 intake — Physics closes 15 November 2026 and Computer Science closes 15 December 2026 — while SINGA is a separate application closing 1 December 2026. Applying early is strongly encouraged: scholarship places are allocated as applications are reviewed, not after the closing date. Official application links:
CS: https://www.comp.nus.edu.sg/programmes/pg/phdcs/application/
Physics: https://www.physics.nus.edu.sg/student/prospective-undergraduates/resear...
Informal enquiries are welcome, and prior quantum/AI experience is helpful but not required: several of the problems we work on are at heart questions about algorithms, optimisation or machine learning.
Full details, funding routes, timelines and contact information: https://yuxuanzhang1995.github.io/join/
