Postdoctoral Research (or Higher-Level) Opportunity in Data Assimilation and AI-enhanced S2S forecast

Job description 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. How to apply 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.