Quantum AI Research Fellow: Quantum Computing & ML

National University of Singapore; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

The National University of Singapore invites applications for the position of Research Fellow in quantum computing and artificial intelligence, in the Department of Computer Science, School of Computing.

The Fellow will collaborate with the Principal Investigator and the wider Singapore quantum AI ecosystem on topics at the interface of quantum information, quantum many-body physics and machine learning, including quantum algorithms and quantum circuit methods.

Qualifications

• PhD in physics, computer science, applied mathematics, or a related field is required or nearing completion.
• Strong research record with publications relevant to quantum information, quantum computation or AI.
• Experience in programming and numerical methods, preferably Python.
• Ability to work independently and as part of a team, with strong communication skills.

Responsibilities

• Conduct high-quality research in quantum computing and AI.
• Collaborate with the Principal Investigator and the wider Singapore quantum AI ecosystem.
• Publish results in peer-reviewed venues and contribute to group projects.

Skills

Analytical thinking

Collaboration

Education

PhD in physics, computer science, applied mathematics, or related field

Tools

Python

Job description

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Research Fellow (Quantum), School of Computing

University-Level Unit: School of Computing Faculty/Department-Level Unit: Department of Computer Science Employee Category: Research Staff Location: Kent Ridge Campus Posted On: 04/09/2026

Job Description

The National University of Singapore invites applications for the position of Research Fellow in quantum computing and artificial intelligence, in the Department of Computer Science, School of Computing (SoC). SoC is strongly committed to research excellence in all its dimensions: Searching for fundamental results and insights in developing novel computational solutions to a wide range of applications, building largescale experimental systems, developing theories and policies for effective management of information systems in organizations, and improving the well-being of society. We seek to play an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems.

The Research Fellow will collaborate closely with the Principal Investigator, Assistant Professor Zhang Yuxuan, as well as with the wider Singapore quantum AI ecosystem. Research topics are at the interface of quantum information, quantum many-body physics and machine learning, and include verifiable quantum advantage and quantum complexity; the classical simulability of quantum circuits using tensor-network and Pauli-path methods; quantum simulation of many-body and open quantum systems on current quantum hardware; and machine-learning methods for quantum circuit compilation and for representing quantum states. Theory-oriented, computational and hardware-facing projects are all available, and there are opportunities to work with industry partners in quantum computing and with collaborators across North America, Europe and Asia. Further details of the group and its current openings are at https://yuxuanzhang1995.github.io/join/ , and informal enquiries to the Principal Investigator are welcome.

Only shortlisted applicants will be notified.

Qualifications

• A PhD in physics, computer science, applied mathematics or a related field, completed or nearing completion
• Research experience in one or more of: quantum information and computation, quantum many-body physics, tensor-network or other numerical methods, and machine learning
• Strong programming skills (for example Python), and the ability to work independently as well as within a team
• A publication record appropriate to career stage

More Information

Location: Kent Ridge Campus

Organization: School of Computing

Department : Department of Computer Science

Employee Referral Eligible: No

Job requisition ID : 34320

Req ID: 34320 Apply now

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