PhD Position in Statistics & Data Science (Robust Methods)

About the role

The ORSTAT research group at KU Leuven seeks a full‑time PhD student to investigate robust statistical methods for improved prediction and anomaly detection. The research will focus on developing methodology for high‑dimensional time series and tensor data, under the supervision of Prof. Christophe Croux, Prof. Stefan van Aelst and Dr. Mia Hubert.

Key responsibilities

• Design and analyse robust statistical algorithms for forecasting and outlier detection.
• Study theoretical properties of the methods both numerically and mathematically.
• Implement algorithms in R and/or Python and apply them to real‑world data sets.
• Contribute to teaching activities, supervise exams (up to 4 hours per week) and mentor junior students.
• Participate in national and international seminars, workshops and conferences.

Required profile

• Master’s degree (or expected graduation in 2026) in Statistics, Data Science, Mathematics, Business Engineering, Economics or a related field.
• Excellent academic record (cum laude or higher).
• Strong interest in statistical theory, coding and practical applications.
• Demonstrated ability to conduct independent research (e.g., an outstanding master’s thesis).
• Excellent spoken and written English and good communication skills.
• Willingness to enrol in the PhD programme of the Faculty of Economics and Business at KU Leuven.

Required skills

• Proficiency in R.
• Proficiency in Python.

What we offer

• A full‑time, one‑year fixed‑term contract starting 1 October 2026, renewable up to four years based on yearly evaluations.
• Competitive salary and benefits in line with Belgian academic standards.
• Access to a dynamic research environment with high international standards.
• Opportunities for personal development, conference participation, doctoral schools and publication.