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.

Hiring Institution: NTU