Job Description
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.
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:
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Develop and implement quantum learning models
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Design and evaluate novel quantum optimization and training algorithms
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Perform large-scale simulations using frameworks such as Qiskit and PennyLane
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Potentially execute experiments on state-of-the-art quantum hardware
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Benchmark quantum models against classical and hybrid baselines
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Contribute to research publications at leading venues
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Develop reusable, high-quality research code and contribute to open-source tools
Qualifications
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Master’s or PhD in Computer Science, Physics, Mathematics, or a closely related field
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Mathematical foundation, particularly in linear algebra, probability, and optimization
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Background or strong interest in quantum computing, quantum information, or quantum algorithms
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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
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Familiarity with quantum software frameworks (e.g., Qiskit, PennyLane, Cirq) is preferred
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Experience with research or advanced technical projects
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Analytical thinking, problem-solving skills, and intellectual curiosity
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Ability to work both independently and collaboratively in a research environment
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Strong scientific writing and communication skills
More Information
Interested applicants should submit the following documents:
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Curriculum Vitae (CV)
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Academic transcripts
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Cover letter (1-2 pages) outlining research interests and relevant experience
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Sample of technical work (e.g., paper, report, or code repository)
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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.
