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.
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