National Taiwan University

Homepage: https://coda.oc.ntu.edu.tw

The Ocean Center at National Taiwan University invites applications for a Postdoctoral Researcher (or higher-level research position) to join a major research initiative on data assimilation and AI-enhanced subseasonal-to-seasonal (S2S) prediction. This project is conducted in close collaboration with the Central Weather Administration (CWA) and focuses on advancing next-generation extended-range forecasting capabilities through a hybrid framework that integrates coupled Earth system modeling, data assimilation, and artificial intelligence.

The successful candidate will work with our in-house GEPSv3 coupled forecast system, a state-of-the-art ocean–atmosphere coupled system designed for extended-range and S2S forecasts. The project aims to improve forecast skill through advanced data assimilation methods, ensemble prediction strategies, and AI-based post-processing and model enhancement techniques. This position offers a unique opportunity to contribute to operationally relevant forecasting research while developing new methodologies at the intersection of physical modeling and machine learning.

Responsibilities

• Develop and implement data assimilation and ensemble initialization strategies within a coupled ocean–atmosphere S2S forecast framework (GEPSv3).
• Conduct subseasonal-to-seasonal prediction experiments, including hindcasts and real-time forecast tests, and assess forecast skill across multiple variables and regions.
• Integrate and process multi-source ocean observational datasets for assimilation and verification.
• Analyze sources of forecast skill and error growth in coupled predictions.
• Collaborate closely with project partners at the Central Weather Administration and contribute to reporting, technical documentation, and research publications.
• Present results at international conferences and contribute to peer-reviewed journal articles.

Preferred Qualifications

• Ph.D. in Atmospheric Science, Oceanography, Climate Science, Applied Mathematics, Data Science, or a related field.
• Demonstrated experience in at least one of the following areas:
  • Data assimilation (e.g., EnKF, 3D/4D-Var, hybrid DA methods)
  • Ensemble prediction systems and forecast verification
  • Subseasonal-to-seasonal or extended-range forecasting
  • Coupled ocean–atmosphere modeling
• Strong skills in scientific programming and numerical computing (Python, Fortran, C/C++, or similar).
• Experience with machine learning / AI frameworks (e.g., PyTorch, TensorFlow, JAX), HPC, or GPU computing is a plus.
• Ability to work independently while collaborating effectively in a multidisciplinary team.
• Strong English communication skills for scientific writing and presentations.

To apply, please send CV, including a list of publication to Prof. Yu-heng Tseng tsengyh@ntu.edu.tw with the subject line “Postdoc Application-DA & AI S2S forecast”. The position will remain open until filled. We strongly encourage applications from candidates of all backgrounds and welcome international applicants.