PhD Positions in Advanced Mathematical Statistics for Non-Euclidean Data Analysis
hace 1 semana
Universidad Carlos III de Madrid and Karlsruhe Institute of Technology are seeking two PhD students to join their research team in the field of mathematical statistics with a focus on non-Euclidean data.
About the ProjectThe 'Stein-based goodness-of-fit Tests for Non-Euclidean Data' (STENED) project is a joint initiative between Universidad Carlos III de Madrid and Karlsruhe Institute of Technology. The project aims to develop cutting-edge mathematical statistics and computational methods for parametric and semiparametric distribution models defined on non-Euclidean supports.
Research FocusThe successful candidates will work on leveraging Stein's method to create an overarching inferential toolbox for non-Euclidean data analysis. They will develop novel statistical methodologies and apply them to real-world problems in collaboration with the project leaders, Dr. Bruno Ebner and Dr. Eduardo García Portugués.
Qualifications and SkillsTo be eligible for this position, applicants must have a Master's degree in Mathematics, Statistics, or a comparable field. A strong academic record, high motivation, and excellent analytical skills are essential. Experience in programming languages such as Python or R is beneficial.
Salary and BenefitsWe offer competitive salaries and benefits, including:
- A gross yearly salary of €41,000 at Karlsruhe Institute of Technology
- A gross yearly salary of €21,000 at Universidad Carlos III de Madrid
- Funding for research stays at both institutions and other universities
- An exciting working environment with motivated colleagues
Candidates should submit their CV, academic records, motivation letter, and a list of two referees to the respective contact persons before the application deadline. Shortlisted candidates will be invited for online interviews.
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