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3–5 Fully Funded PhD Positions in Quantum Computing & Artificial Intelligence (National University of Singapore)

PhD position

9/14/2026

Opportunity at a glance

  • Position: 3–5 fully funded PhD students in Quantum Computing and Artificial Intelligence

  • Host: National University of Singapore (NUS), Singapore

  • Departments: School of Computing and Department of Physics

  • Funding: Fully funded PhD places (scholarship + stipend)

  • Eligibility: Strong background in quantum computing, quantum many‑body physics, tensor networks, and/or machine learning; Master's or equivalent preferred

  • Deadlines:

    • Physics (PhD): 15 November 2026

    • Computer Science (PhD): 15 December 2026

    • SINGA scholarship (separate): 1 December 2026

  • Expected start: August 2027

  • Location: Singapore

Why this PhD opportunity matters

Quantum computing and artificial intelligence are two of the most transformative technologies of our time.

Quantum computing promises to solve certain problems (e.g., quantum many‑body simulation, optimisation, cryptography) that are intractable for classical computers.

Artificial intelligence, especially deep learning and modern ML, is reshaping how we:

  • Analyse complex data

  • Discover patterns in high‑dimensional spaces

  • Design and control physical and computational systems

At their intersection lie exciting research directions such as:

  • Using ML to understand and control quantum systems

  • Applying quantum algorithms to accelerate ML

  • Developing hybrid quantum‑classical models for scientific computing

  • Using tensor networks and quantum‑inspired methods for large‑scale ML and physics

As a PhD student, you will work on problems that are both theoretically deep and computationally cutting‑edge, with potential impact on quantum technologies, scientific computing, and AI.

Research themes you might work on

Specific projects will be shaped by your background and interests, but typical research directions in the group include:

Quantum computing & quantum information

  • Design and analysis of quantum algorithms

  • Quantum error correction and fault‑tolerant architectures

  • Quantum simulation of many‑body systems

  • Resource estimation and complexity analysis

Quantum many‑body physics

  • Entanglement structure and phase transitions

  • Non‑equilibrium dynamics and thermalisation

  • Open quantum systems and decoherence

  • Connections between many‑body physics and quantum information

Tensor networks & numerical methods

  • Matrix product states (MPS), projected entangled pair states (PEPS), MERA, and related ansatze

  • Tensor‑network methods for ground states, dynamics, and finite‑temperature problems

  • Quantum‑inspired classical algorithms for high‑dimensional problems

Machine learning & AI for quantum science

  • Using neural networks to represent quantum states and dynamics

  • ML‑assisted discovery of phases of matter and order parameters

  • Reinforcement learning for quantum control and circuit optimisation

  • Data‑driven modelling of quantum devices and experiments

Quantum‑enhanced or quantum‑inspired ML

  • Quantum algorithms for linear algebra, optimisation, and sampling

  • Variational quantum algorithms (VQE, QAOA, quantum neural networks)

  • Classical analogues inspired by quantum structures (e.g., tensor‑network ML models)

You will be expected to develop strong theoretical foundations alongside advanced computational skills, and to produce research that can be published in top venues in quantum information, physics, and/or machine learning.

Who should apply

Required background:

  • A Master's degree (or equivalent) in:

    • Physics

    • Computer Science

    • Applied Mathematics

    • Or a closely related field

  • Strong foundation in at least one of:

    • Quantum information and computation

    • Quantum many‑body physics

    • Tensor‑network or other advanced numerical methods

    • Machine learning / deep learning

  • Demonstrated research potential, e.g. through:

    • A strong Master's thesis

    • Publications or preprints (if any)

    • Substantial research projects or internships

Additional advantages:

  • Experience with:

    • Programming in Python, C++, Julia, or similar

    • Numerical libraries and frameworks (e.g., NumPy, PyTorch, TensorFlow, JAX, ITensor, TeNPy)

    • High‑performance computing or GPU computing

  • Familiarity with:

    • Quantum computing frameworks (Qiskit, Cirq, Pennylane, etc.)

    • Scientific computing and simulation of physical systems

  • Strong mathematical background in:

    • Linear algebra

    • Probability and statistics

    • Optimisation

Fluent English (written and spoken) is required for research and coursework.

Funding & benefits

These are fully funded PhD positions, meaning:

  • Tuition fees are covered by the scholarship

  • You receive a monthly stipend sufficient to cover living expenses in Singapore (exact amount depends on the specific scholarship and university rules)

  • Additional benefits may include:

    • Conference travel support

    • Access to HPC resources and computing clusters

    • Participation in workshops, schools, and collaborations

NUS PhD students typically:

  • Enrol in a structured PhD programme with coursework in the first year

  • Work closely with their supervisor and research group

  • Have opportunities for international collaborations and visits

  • Can participate in teaching (with additional remuneration, depending on the scheme)

Exact terms (stipend level, duration, teaching expectations) depend on the specific scholarship and department.

Application routes & deadlines

There are multiple application routes, each with its own deadline:

1. NUS PhD in Physics (Quantum Computing & AI)

  • Department: Department of Physics, NUS

  • Intake: August 2027

  • Deadline: 15 November 2026

  • Notes:

    • Apply through the NUS Physics PhD application portal.

    • Indicate your interest in working with A/Prof Yuxuan Zhang and in quantum computing & AI.

    • Applying early is strongly encouraged: scholarship places are allocated as applications are reviewed, not only after the closing date.

2. NUS PhD in Computer Science (Quantum Computing & AI)

  • Department: School of Computing, NUS

  • Intake: August 2027

  • Deadline: 15 December 2026

  • Notes:

    • Apply through the NUS School of Computing PhD application portal.

    • Clearly state your interest in quantum computing and AI, and your preference to work with A/Prof Yuxuan Zhang.

    • Early application is again recommended due to rolling scholarship allocation.

3. SINGA (Singapore International Graduate Award)

  • What it is: A prestigious, competitive scholarship for international PhD students in Singapore, covering tuition and providing a generous stipend.

  • Deadline: 1 December 2026 (for the relevant intake cycle)

  • Notes:

    • SINGA is a separate application from the departmental PhD applications.

    • You can (and should) apply to SINGA in parallel with your NUS departmental application.

    • In your SINGA application, indicate your preferred supervisors and research area (quantum computing & AI at NUS, A/Prof Yuxuan Zhang).

Application links (for reference):

Always check the latest instructions on the official NUS and SINGA websites, as procedures can change.

How to apply

  1. Review the research themes and confirm that your background aligns with quantum computing, quantum many‑body physics, tensor networks, and/or machine learning.

  2. Prepare your application materials, typically including:

    • Cover letter / statement of purpose describing:

      • Your motivation for pursuing a PhD in quantum computing & AI

      • Your relevant background (courses, projects, thesis, publications)

      • Why you want to work with A/Prof Yuxuan Zhang at NUS

    • Curriculum Vitae (CV), including:

      • Education (degrees, institutions, graduation dates, GPA if strong)

      • Research experience (projects, internships, thesis topics)

      • Publications, preprints, conference presentations (if any)

      • Technical skills (programming languages, frameworks, numerical methods)

      • Contact information for 2–3 referees (usually academic)

    • Academic transcripts from Bachelor's and Master's degrees

    • Research statement / proposal (if required by the department or scholarship):

      • Outline of your research interests

      • Possible directions you would like to explore (quantum algorithms, tensor networks, ML for quantum, etc.)

    • English proficiency proof (if required; e.g., TOEFL/IELTS for non‑native speakers)

  3. Submit your departmental PhD application:

    • For Physics: via the NUS Physics/Graduate School portal, by 15 November 2026.

    • For Computer Science: via the NUS School of Computing portal, by 15 December 2026.

  4. Submit your SINGA application (if you are an international candidate and wish to be considered for this scholarship):

    • Via the official SINGA portal, by 1 December 2026.

  5. In all applications, clearly mention:

    • Your interest in quantum computing and AI

    • Your preference to work with A/Prof Yuxuan Zhang at NUS

    • Any specific sub‑areas you are most excited about (e.g., tensor networks, quantum many‑body, ML for quantum)

If you have questions before applying, you can:

  • Check the group website / lab page (if available) for more details on current projects

  • Contact the supervisor or group via email with a concise enquiry and your CV (optional but sometimes helpful)

Recruitment timeline

  • Call opened: August 2026 (positions advertised on Quantiki and related platforms)

  • Physics PhD deadline: 15 November 2026

  • SINGA deadline: 1 December 2026

  • Computer Science PhD deadline: 15 December 2026

  • Expected start: August 2027

Applications are reviewed on a rolling basis, and scholarship places are allocated as applications come in. Applying early improves your chances.

How we can help

If you're considering these NUS PhD positions:

  • We can help you assess fit between your background (quantum, many‑body, tensor networks, ML) and the group's research themes.

  • Your mentor can help you craft a targeted statement of purpose / research statement that:

    • Clearly explains your interest in quantum computing & AI

    • Highlights relevant projects (thesis, coursework, internships, publications)

    • Connects your skills (numerical methods, coding, maths, physics) to specific research directions

  • We can review your CV and research statement to emphasise:

    • Quantum and ML experience

    • Numerical and computational skills

    • Research potential and independence

Interested? Share a draft CV and any notes on relevant projects (especially quantum, many‑body, tensor networks, or ML work), and we'll help you turn this into a strong, submission‑ready application before the November/December deadlines.

For more personalized tips or templates contact our team.

www.applywithmentors.com