Job Description

The successful candidate will work with Asst. Prof. Shen Shuting on combinatorial inference under a project on "Post-learning inference for near-optimal discrete structures".

The main responsibilities of the position include: Theoretical derivations, numerical experiments, real data applications, paper writing

Qualifications / Discipline:  
•    PhD in Statistics, Data Science, Operations Research, Applied Mathematics, Computer Science, or a closely related field. 
•    Candidates in the final stages of their PhD studies may also be considered.

Skills:  
•    Strong technical background in probability, statistics, optimization, or related theoretical areas.
•    Demonstrated ability to conduct rigorous mathematical derivations and develop theoretical results.

Experience:   
•    Prior research experience in theoretical statistics, statistical machine learning, high-dimensional inference, empirical process theory, stochastic modeling, optimization, or related areas. 
•    Experience with writing and developing theoretical research papers is highly desirable.