Visiting Research Fellow for Quantum Algorithms

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading university seeks a quantum computing researcher to develop quantum algorithms for generative diffusion models using cutting-edge quantum techniques. The role involves both theoretical and practical aspects of quantum computing, requiring a PhD-level understanding of quantum algorithms and experience with quantum programming frameworks. Collaborate with experts while working on the latest innovations in quantum machine learning.

Qualifications

• Strong foundation in quantum algorithms and path integral methods.
• Experience with quantum hardware platforms, preferably Quantinuum.
• Background in quantum machine learning or quantum statistical mechanics.

Responsibilities

• Extend existing quantum path integral algorithms for diffusion model settings.
• Develop and test prototype quantum circuits on real quantum devices.
• Present results to both technical and non-technical stakeholders.

Skills

Quantum algorithms

Simulations

Path integral methods

Analytical skills

Education

PhD in Quantum Computing or equivalent

Tools

Qiskit

Cirq

Quantinuum platforms

Job description

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

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 strong quantum computing researcher to develop quantum algorithms for generative diffusion models using path integral formulations. This project aims to advance quantum machine learning by:

• Designing a quantum counterpart of diffusion models;
• Leveraging path integral methods to model stochastic differential equations (SDEs);
• Extending recent quantum simulation techniques to accommodate non-physical processes found in generative diffusion modeling;
• Demonstrating a prototype of the quantum algorithm on Quantinuum hardware.

This candidate will contribute to both theoretical development (e.g., complexity analysis and algorithm design) and practical implementation (quantum circuit prototyping and execution)

Key Responsibilities

• Extend existing quantum path integral algorithms to diffusion model settings;
• Formulate and prove complexity theorems for the new algorithms;
• Develop and test prototype quantum circuits for small-scale systems;
• Collaborate with hardware and simulation experts to run experiments on real quantum devices;
• Document and present results to both technical and non-technical stakeholders.

Job Requirements

• PhD or equivalent research experience in Quantum Computing, Theoretical Physics, Applied Mathematics, or a closely related field;
• Strong foundation in quantum algorithms, particularly simulation and path integral methods;
• Familiarity with stochastic processes, diffusion models, or generative AI;
• Proficiency in quantum programming frameworks (e.g., Qiskit, Cirq, or Quantinuum’s platforms);
• Strong analytical skills and ability to work independently on cutting-edge research problem;
• Experience with quantum hardware platforms (especially Quantinuum);
• Background in quantum machine learning or quantum statistical mechanics · Prior publications or demonstrated experience in quantum algorithm design.