Doctoral degree program Applied Mathematics (abbr. AM) at FMPI reflects the need of the labor market for enough graduates mastering not only basic mathematical disciplines, but also being able to apply mathematical knowledge in other sciences such as physics, biomathematics, theoretical economics and finance. These applied disciplines require deepening and expanding of the mathematical methods and creating new high-quality models. At the same time, they require mastery of modern software tools for performing scientific and technical calculations. The PhD program Applied Mathematics has the ambition to combine deep mathematical knowledge in the field of mathematical analysis, statistics and mathematical modeling with the acquisition of knowledge from frontier scientific disciplines.
Study partThe focus of the study part is the individual study of literature designated by the supervisor. Part of the study can also be attending the lectures in selected subjects. Another part of the study is active participation in regular scientific seminars, the selection of which for the doctoral student is determined by the supervisor. At the same time, the evaluation of the PhD student may include his/her participation in domestic and international conferences and summer/winter schools, giving a talk at a conference and publication of an article in a peer-reviewed journal. Within the study part of the program, the student must complete doctoral lectures worth in total at least 40 credits, but not more than 70 credits.
The courses in Probability Theory, Random Dynamical Systems, Nonlinear Statistical Models and Simulation Methods are suitable for PhD students who focus on probability theory and mathematical statistics.
By completing the courses in Asymptotic Methods, Fluid Flow Models, Biomatematics and Fundamentals of Mathematical Modeling in the Empirical Sciences, the student will gain knowledge of modern methods of mathematical modeling and analysis of models in the natural and physical sciences.
For PhD students focused on financial mathematics and mathematical economics, it is recommended to take the courses Analysis of Financial Mathematics Models, Probabilistic Modeling in Insurance and Selected Parts of Financial Mathematics.
Completion of the courses Internal Point Methods in Linear Programming and Modern Methods of Convex Optimization is recommended for doctoral students with a focus on modern optimization methods.
Scientific partThe focus of the scientific part is the writing of a dissertation thesis. The work should prove the doctoral student's readiness to work scientifically by providing either an original mathematical result or an original application of mathematical theory in a selected scientific discipline, such as physics, biomatematics, theoretical economics and mathematical theory of finance. The result of the work should be publishable in a peer-reviewed scientific journal in the field of mathematics or in the subject area of its application. The student is encouraged to present his/her scientific results at a domestic or international conference. All these activities are properly credited in the study program.
Full-time doctoral students who have permanent residency in the European Union are entitled to receive a scholarship for the entire standard duration of their studies. The scholarships are paid starting on the date of enrollment. The monthly scholarship as of September 1, 2023 is determined according to the applicable legislation as follows:
Doctoral studies are considered an equivalent to full time employment and in the majority of cases cannot be combined with another employment. Job holding applicants who intend to keep their job are advised to apply for the external (distance) form of doctoral studies. Doctoral students enrolled in the regular form are expected to participate in teaching activities such as conducting recitations or exam grading, in accordance with the needs of their corresponding departments.
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Martin Hurban - Data Science Team Leader at ČSOB bank; graduate of MEFM (master's program) and AM
“In 2015, I graduated with a degree in Mathematics of Economy, Finance, and Modelling at the FMPI CU.
Throughout my time at MEFM, I was immersed in algorithmic thinking and gained a robust mathematical grounding, enabling rapid assimilation into various scientific fields.
This foundation fostered my ability to learn in a structured manner, an incredibly valuable skill in today's world.
My academic journey was enriched by inspiring lecturers and a supportive group of peers, who were instrumental in honing my analytical and communicative abilities.
Upon completing my master’s programme, I progressed to a PhD in Applied Mathematics, focusing on the modelling of solidification of liquids.
After my doctoral studies, I pivoted professionally, joining ČSOB bank as a data scientist.
There, my work centred on devising predictive models for customer behaviour and refining algorithms for geographic data analysis.
Subsequently, I was engaged in text processing and the development of virtual assistants at KBC (the parent company of ČSOB).
Pursuing this programme has opened up a plethora of applications, empowering me to select my preferred field of interest.”
