We are hiring 1 Postdoctoral Fellow in dynamical system theory and machine learning for extreme weather forecasting applications. The ideal candidate should be skilled in coding, and software development, and be highly proficient in Python, large-scale spatio-temporal data analysis (ideally the ERA5 and other reanalysis datasets), dynamical system theory, reduced order modelling (including POD, SPOD and Autoencoders), and neural networks. The project is in collaboration with several partner institutions: ECMWF , Argonne National Laboratory (USA), CNRS (France), and University of Cambridge (United Kingdom), the latter starting from 2023. The primary objective of the project is to provide a fast computational framework for extended-range extreme weather forecasts, as well as quantify damage and develop mitigation strategies for extreme weather events.

Job requirements

  • PhD in Computer Science, Applied Mathematics, Physics, Engineering, or related fields.
  • Coding and software development (Python, Tensorflow or Pytorch).
  • Neural newtork interpretability.
  • Natural Language Processing.
  • Neural networks.
  • Large-scale spatio-temporal data analysis.
  • Weather and climate.
  • Good problem-solving skills.
  • Proficient in English writing and verbal communication skills.

Location and conditions

The position is based at the National University of Singapore (NUS), College of Design and Engineering Singapore, 21 Lower Kent Ridge Road, 119077.

Salary range: S$ 4800-5800/month

Contact us

If you are interested in joining us, please email us your CV. In the CV, please include: education background, working experience, list of publications, and at least 3 references that can provide recommendation letters.
Our group thank all applicants for their interest, however only those candidates selected for interviews will be contacted.