Doctoral Studies

Probability, Statistics and Mathematical Modelling - Field

Brief description of field

This field of study is designed for students with a strong interest in probability theory, mathematical statistics, or their applications. It provides students with a theoretical knowledge of the basic principles and methods of probability theory, mathematical statistics, and statistical data analysis. It will allow the students to gain deeper understanding of certain areas of the studied theories. The student will also be acquainted with modern methods of data processing and stochastic modelling, including the use of the latest calculation systems.

Objectives of the study programme

The field of Probability, Statistics, and Mathematical Modelling is designed to provide students with a comprehensive education in modern applied as well as theoretical fields of contemporary mathematical statistics and probability theory. It should also prepare them for scientific work in these fields. Additionally it should teach them how to modify and develop new methods of data analysis, create adequate software, and describe events using probabilistic and stochastic models.

Profile of a typical graduate

The graduate will acquire good theoretical knowledge to work in theoretical and applied research. He/She will be able to model real events and processes using stochastic modelling, will be capable of independent scientific work in mathematical statistics and probability theory. The graduate will find jobs in institutions where modelling of real events/processes is needed and where modern specialized statistical software is created. He/She will also find employment in institutions that are focused on theoretical research of probabilistic and statistical methods.

Requirements for applicants

Applicants should have a Masters degree in mathematics or applied mathematics, or any other field of study in combination with mathematics. In special cases students from other non-mathematical fields may be accepted. Such applicants, however, must be familiar with the theory of probability and mathematical statistics at a Masters Degree level (i.e. basic courses studied in the fields of Mathematics or Applied mathematics). Alternatively the student will need to complete these courses at the beginning of the doctoral studies. Active knowledge of one foreign language, preferably in English, and passive knowledge of another foreign language is required.

Study requirements and completion of studies

Individual Study Plan

The student will need to completes six one-semester courses appointed for doctoral studies.
After consultation with the supervisor, self-study will focus on gaining more knowledge in the field and on special aspects needed to write a good dissertation. The student will also regularly attend seminars and help with preparing/teaching undergraduate courses.

Content and scope of the state doctoral examination, required knowledge

Knowledge of probability theory, mathematical statistics, and related fields according to the focus of the dissertation will be examined. The extent of the State Doctoral Examination is determined by the successfully completed subjects/courses from blocks A and B. Three subjects will be selected in order to cover the full extent of the studied field and the specialization chosen for one’s dissertation, and the exam will focus on these subjects.

Requirements for a doctoral dissertation

The thesis must contain original and published results or results accepted for publication. It is advised that some of the results be presented at an international conference.

General Topics for PhD theses:

  • Elliptically Contoured Distributions and their use
  • Qualitative properties of solutions to stochastic differential equations
  • Multivariate generalized linear models
  • Density estimation using wavelets and other orthogonal systems
  • Spectral techniques in data analysis

A List of current dissertation topics for the academic year is found on the page below.

Individual study plan

The student will need to completes six one-semester courses appointed for doctoral studies.
After consultation with the supervisor, self-study will focus on gaining more knowledge in the field and on special aspects needed to write a good dissertation. The student will also regularly attend seminars and help with preparing/teaching undergraduate courses.

List of members of doctoral committee

List of supervisors

Commission for state doctoral exams and defenses

List of current doctoral topics

Department pages


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