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.