The successful candidate will work with Dr. Pavel TKALICH on Coastal Hydrodynamic, Ocean Dynamics, Water Quality and Ecosystem Modelling, Environmental Impact Assessment, under soon-to-be funded projects on Dispersion of Pollutants in Singapore Coastal Waters and South-East Asia.  

The main responsibilities of the position include:

Development and application of Machine Learning/Data Driven methods for fast solution of broad range of Coastal, Ocean and Environmental  problems.

Qualifications / Discipline:

Ph.D. or Master’s degree from reputable universities in Oceanography, Coastal Science and Engineering,  Data Science, or other related disciplines. Level of appointment and remuneration commensurate with the candidate’s experience.

Skills:

• Development and implementation of machine learning / data driven models to analyze and interpret coastal oceanographic data.
• Experience may include: (a) Machine Learning,  like decision trees, support vector machines, and neural networks; (b) Statistical Analysis, including as regression analysis, hypothesis testing, and ANOVA; (c) Data Mining, including clustering, association rule mining, and anomaly detection.
• Contribution to the advancement of predictive data driven models for coastal ocean processes, including wind-waves, currents,  sea level extremes, coastal erosion, and marine ecosystem dynamics.