Research Assistant (Sparse Boosting and Spatial Data Analytics)

The School of Physical and Mathematical Sciences at NTU Singapore is seeking a Research Assistant to support an AcRF Tier 1 project on sparse boosting for high-dimensional spatial autoregressive models. The role involves methodological development, simulations, computational implementation, real-data applications, and preparation of reproducible research outputs.

• 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.

• 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.