About the role
AI summarisedThis role is for a Senior Research Scientist at I2R, focusing on AI-enabled localized tropical weather prediction. The scientist will develop machine learning and deep learning models for hazardous weather forecasting using multi-modal data, and translate research into operational solutions for aviation and maritime safety.
ResearchFull-time
Key Responsibilities
- Conduct cutting-edge, data-driven research on tropical convective hazard prediction using multi-modal datasets from weather observation systems and Numerical Weather Prediction (NWP) models.
- Develop, implement, and evaluate advanced machine learning and deep learning models for multi-source, multi-scale weather forecasting.
- Leverage state-of-the-art AI techniques to improve the accuracy and spatio-temporal resolution of hazardous weather predictions such as heavy precipitation, strong winds, and lightning.
- Translate research breakthroughs into operationally deployable solutions.
- Work in a multi-disciplinary team comprising atmospheric scientists and operational stakeholders.
- Deliver actionable hazard intelligence to support real-world applications, including safer and more efficient air and ground operations in tropical environments.
Requirements
- PhD or equivalent experience in Computer Science, Data Science, Atmospheric Science, Meteorology, Physics, Mathematics, or related field.
- Strong background in machine learning and deep learning.
- Experience with weather forecasting or numerical weather prediction models.
- Proficiency in Python and deep learning frameworks such as TensorFlow or PyTorch.
- Experience working with multi-modal and spatio-temporal data.
- Ability to conduct independent research and publish in top-tier venues.
- Excellent communication and collaboration skills for working in a multi-disciplinary team.
- Experience in translating research into operational systems is a plus.