Research Assistant in Quantum Algorithms and Machine Learning

Job Title: Research Assistant in Quantum Algorithms and Machine Learning

University-Level Unit: Centre for Quantum Technologies

Faculty/Department-Level Unit: Exploratory Initiatives Group

Employee Category: Research Staff

Location_ONB: Kent Ridge Campus

Posting Start Date: 14/04/2026

About the Centre for Quantum Technologies (CQT)

The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in this new discipline of quantum technologies are applying their discoveries in computing, communications, and sensing.

CQT is hosted by the National University of Singapore. The Centre also has staff at the Agency for Science, Technology and Research, Nanyang Technological University, Singapore, and the Singapore University of Technology and Design. With some 200 staff and students, it offers a friendly and international work environment

Learn more about CQT at https://www.cqt.sg/

Job Description

We are seeking a promising Research Assistant to join an advanced research project at the intersection of quantum computing and machine learning, focused on developing scalable and coherent training methods for quantum models.

This project tackles one of the central challenges in quantum machine learning: how to train quantum systems efficiently and reliably on scaling quantum hardware. The research will develop novel optimization frameworks based on quantum dynamics and apply them to advanced learning architectures.

The successful candidate will contribute to both theoretical advances and experimental implementations, with opportunities to co-author publications and engage with leading researchers in the field.

Main Responsibilities:

Develop and implement quantum learning models

Design and evaluate novel quantum optimization and training algorithms

Perform large-scale simulations using frameworks such as Qiskit and PennyLane

Potentially execute experiments on state-of-the-art quantum hardware

Benchmark quantum models against classical and hybrid baselines

Contribute to research publications at leading venues

Develop reusable, high-quality research code and contribute to open-source tools

Qualifications

Master’s or PhD in Computer Science, Physics, Mathematics, or a closely related field

Mathematical foundation, particularly in linear algebra, probability, and optimization

Background or strong interest in quantum computing, quantum information, or quantum algorithms

Knowledge of machine learning (e.g., deep learning, optimization, or learning theory)

Programming skills in Python and experience with scientific computing (e.g., NumPy, SciPy, PyTorch)

Experience with numerical simulations, algorithm design, or high-performance computing is advantageous

Familiarity with quantum software frameworks (e.g., Qiskit, PennyLane, Cirq) is preferred

Experience with research or advanced technical projects

Analytical thinking, problem-solving skills, and intellectual curiosity

Ability to work both independently and collaboratively in a research environment

Strong scientific writing and communication skills

More Information

Interested applicants should submit the following documents:

Curriculum Vitae (CV)

Academic transcripts

Cover letter (1-2 pages) outlining research interests and relevant experience

Sample of technical work (e.g., paper, report, or code repository)

Contact information for 2 referees (Letters may be requested at a later stage)

For more information, please reach out to lpira@nus.edu.sg

We encourage applications from candidates with diverse backgrounds. Applicants who do not meet all the listed criteria but are interested in the role are encouraged to apply.