Postdoctoral Researcher in High-dimensional Data Analysis
hace 1 semana
We are seeking a highly motivated postdoctoral researcher to join our team at The International Society for Bayesian Analysis. The successful candidate will work on various topics related to the analysis of complex high-dimensional data, including new directions in high-dimensional statistics, statistical learning for non i.i.d. data, change-point detection, deep learning, and stochastic gradient descent.
The scope of the project is broad and allows for sub-projects related to mathematical statistics and statistical learning theory, Bayesian statistics, theory of neural networks, and Malliavin calculus. The primary supervisor will be Eulalia Nualart, with collaborations with other professors of the Statistics group at UPF and the BSE Data Science Center possible.
Key responsibilities will include developing and implementing new statistical methods, analyzing complex data sets, and publishing research findings in top-tier journals. The ideal candidate will have a strong background in statistics, machine learning, and programming skills in languages such as R or Python.
Interested candidates should submit their application, including a CV and a short research statement, to Lorenzo Cappello. Three referees should also send a letter of reference on their behalf.
The application deadline is October 31st, 2022.
Key Requirements
- Ph.D. in Statistics, Machine Learning, or a related field
- Strong background in statistical learning, Bayesian statistics, and high-dimensional data analysis
- Excellent programming skills in R or Python
- Strong publication record in top-tier journals
- Excellent communication and teamwork skills
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