Job Description

Mengaldo’s Laboratory is looking for a self-motivated, proactive and highly creative 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), natural language processing and neural networks.

The project is in collaboration with 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.

Qualifications

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

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Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.

More Information

Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department: Mechanical Engineering
Employee Referral Eligible: No
Job requisition ID:17418