Quantum ML Research Fellow - Classical-Quantum Algorithms

National University of Singapore; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

National University of Singapore invites applications for a Research Fellow (Quantum Machine Learning) in the College of Design and Engineering, Mechanical Engineering. The position focuses on integrating classical ML with quantum approaches to advance simulations in drug discovery and molecular modelling.

The successful candidate will join a multidisciplinary team developing both quantum and classical algorithms, with robust production-grade software implementations and strong collaboration

Qualifications

• Proficient in machine learning methods and frameworks.
• Experience with quantum machine learning concepts.
• Understanding of dynamical systems theory and simulations.
• Knowledge of algorithms for simulating classical dynamical systems (e.g., transport, multiscale flows).
• Experience with signal processing and time-evolution methods.

Responsibilities

• Collaborate on integrating classical ML with quantum algorithms for research in drug discovery and molecular modelling.
• Develop and implement robust, production-grade software for quantum/classical workflow.
• Contribute to the design and evaluation of quantum and/or classical algorithms in multidisciplinary teams.

Skills

Machine learning

Quantum Machine Learning

Dynamical Systems

Algorithms for dynamical systems

Signal processing

Job description

National University of Singapore invites applications for a Research Fellow (Quantum Machine Learning) in the College of Design and Engineering, Mechanical Engineering. The position focuses on integrating classical ML with quantum approaches to advance simulations in drug discovery and molecular modelling.

The successful candidate will join a multidisciplinary team developing both quantum and classical algorithms, with robust production-grade software implementations and strong collaboration