Research Fellow (Quantum Machine Learning)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Quantum-Machine-Learning%29/33800-en_GB/ We regret that only shortlisted candidates will be notified. 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