Research Engineer (Machine Learning) 1

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

The National University of Singapore invites excellent candidates to join a collaborative research initiative between the MathEXLab (Mechanical Engineering) and the Centre for Quantum Technologies (CQT). The role involves developing classical and quantum algorithms, software implementations, and applications in drug discovery and molecular modelling within a multidisciplinary team.

The project benefits from access to leading experts and advanced quantum computing infrastructure to push forward

Qualifications

• Proficiency in machine learning and ML algorithms.
• Expertise in quantum machine learning concepts and methods.
• Understanding of dynamical systems theory and modeling.
• Experience with algorithms for simulating classical dynamical systems (e.g., transport, multiscale flows).
• Knowledge of signal processing, time evolution, and structure-preserving transformations.

Responsibilities

• Collaborate in a multidisciplinary team on classical and quantum algorithm design.
• Implement software prototypes and production-grade research code.
• Apply methods to drug discovery and molecular modelling.

Skills

Machine learning

Quantum Machine Learning

Dynamical Systems

Algorithms for dynamical systems

Signal processing

Job description

Job Description

We invite excellent candidates in classical machine learning to join a collaborative research initiative between the MathEXLab of NUS (Mechanical Engineering) and the Centre for Quantum Technologies (CQT). The project benefits from access to both leading experts in the field and advanced quantum computing infrastructure. The successful candidate will work within a multidisciplinary team that combines classical and quantum algorithm design, software implementation, and applications in drug discovery and molecular modelling. The research will contribute to the development of both quantum and/or classical algorithms, supported by robust, production-grade implementations.

Qualifications

• Machine learning
• Quantum Machine Learning
• Dynamical Systems
• Algorithms for the simulation of classical dynamical systems (including climate-relevant targets such as transport, multiscale flows, and extremes)
• Signal processing, time evolution, and structure-preserving transformations