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We are seeking highly motivated postdoctoral researchers to join our team and contribute to various projects related to high-dimensional data analysis. Our research interests include statistical learning for non-independent data, change-point detection, deep learning, and stochastic gradient descent.
The ideal candidate will have a strong background in mathematical statistics, statistical learning theory, Bayesian statistics, or neural networks. Sub-projects focusing on Malliavin calculus, theoretical aspects of machine learning, and applications to real-world problems are also encouraged.
Our research group collaborates with renowned experts in the field, ensuring a stimulating environment for professional growth and knowledge exchange.
- Job Type: Full-time
- Duration: One year
Qualified candidates should submit their updated CV, a concise research statement, and three letters of recommendation. The deadline for application is October 31st.
