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National University of Singapore's Centre for Quantum Technologies at Kent Ridge Campus seeks a Research Assistant to advance quantum algorithms and machine learning, tackling scalable training for quantum models.
You will develop models, implement training methods, run large-scale simulations with Qiskit/PennyLane, and contribute to publications.
The role offers collaboration with leading researchers and hands-on work with state-of-the-art hardware and software.
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: 06/07/2026
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