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, mathematical modelling or their applications. It provides students with a theoretical knowledge of the basic principles and methods of probability theory, mathematical statistics, statistical data analysis, and mathematical modelling. 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, deterministic and stochastic modelling, including the use of the latest computational 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, probability theory, deterministic or stochastic modelling. 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, deterministic or 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 deterministic or stochastic modelling, will be capable of independent scientific work in mathematical statistics, probability theory, deterministic or stochastic modelling. 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 Master 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 Master 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. For admission, the candidate must receive a minimum of 120 points from 200 (expertise in the field 60 points from 100, language skills 60 points from 100).

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. 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. The subjects will be selected from the following list: Parametric statistical inference, Nonparametric statistical inference and smoothing, Regression models, Computational statistics and multivariate statistical analysis, Probability theory, Deterministic processes. The necessary condition for submitting the application for the state doctoral examination is the fulfillment of all the duties stipulated by the Doctoral Board.

Requirements for a doctoral dissertation

The thesis must contain original results published abroad or results accepted for publication. It is crucial that some of the results are presented at international conferences.

General Topics for PhD theses:

  • Survival analysis and regression models for time-to-event data.
  • Kernel smoothing and statistical inference for spherical data.
  • Stochastic models in neuroscience.
  • Analysis of functional data, spatial and spatio-temporal data.
  • Statistical inference in life and non-life insurance.
  • Qualitative properties of solutions to stochastic differential equations.

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

Individual study plan

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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