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Job Description
The successful candidate will work with Assoc. Prof. Li Cheng on scalable Bayesian Gaussian process modeling for spatiotemporal data under a project on “Enhancing Scalability of Bayesian Gaussian Process Models”.
The main responsibilities of the position include:
- literature review on the statistical methodology of modeling non-Gaussian data;
- developing new Bayesian Gaussian process based models and scalable computational algorithms for non-Gaussian spatial and spatiotemporal data;
- coding and conducting numerical experiments related to the main topic.
Qualifications
• Qualifications / Discipline:
Recognised Bachelor / Master degree in Mathematics, Statistics, Data Science and related fields.
• Skills:
- Familiar with the methodology and computation of Gaussian processes;
- Strong programming skills in R, Rcpp, or Julia.
• Experience:
Nil
