Research Assistant (Sparse Boosting And Spatial Data Analytics)

The School of Physical and Mathematical Sciences at NTU Singapore conducts research and education across the physical and mathematical sciences. The Division of Mathematical Sciences is seeking a Research Assistant to support an AcRF Tier 1 project on sparse boosting for high-dimensional spatial autoregressive models. The successful candidate will contribute to methodological development, simulations, computational implementation, real-data applications, and preparation of reproducible research outputs. Key Responsibilities: Develop and implement sparse boosting methods for high-dimensional spatial models. Conduct simulation studies, benchmarking, robustness checks, and computational optimisation. Apply the methods to real-world datasets and prepare code, reports, presentations, and manuscripts. Collaborate with the PI and research partners and support project milestones and reporting. Job Requirements: Minimum Bachelor degree in Statistics, Data Science, Mathematics, Computer Science, Econometrics, or a related field. Strong background in statistical modelling, high-dimensional data analysis, and machine learning. Proficiency in R; Python or related computational experience is advantageous. Good analytical, programming, communication, and scientific-writing skills. Able to work independently and collaboratively and meet project timelines. We regret to inform that only shortlisted candidates will be notified.