Lund University

Overview

The Mathematical Statistics program at Lund University delves into the realms of probability and statistical inference, equipping students with the expertise to analyze uncertainty and data effectively. This advanced course focuses on developing sophisticated skills in modeling random phenomena and applying stringent methods to address real-world research challenges.

What you'll study

This program integrates advanced coursework with hands-on research training, allowing students to tailor their study plans according to their research interests. The curriculum encompasses the core theoretical foundations of contemporary statistical inference, including:

• Asymptotic Theory
• Likelihood Theory
• Bayesian Inference
• Time Series Analysis
• Nonparametric Inference
• Robust Inference
• Inference for Stochastic Processes

Throughout the program, students will refine a research problem, perform literature reviews, engage in methodological work, and present their findings through seminars and written or oral reports. Depending on the chosen pathway, completion of a thesis or dissertation may also be required.

Entry requirements

To be eligible for the Mathematical Statistics program, applicants must fulfill the general admission criteria for third-cycle (doctoral) studies at Lund University. Typically, this requires holding a relevant second-cycle qualification, such as a Master's degree, or possessing substantially equivalent knowledge.

Applicants should have a strong academic background in mathematical statistics, probability theory, and statistical inference. Admission is competitive, based on a holistic assessment of qualifications and research suitability.

Career prospects