To advance from the first year to the second year, the doctoral student must achieve at least 30 ECTS credits from the first year, have an approved doctoral dissertation topic and must submit the doctoral dissertation thesis proposal, which is confirmed by their mentor’s signature on the appropriate form.

To advance from the second to the third year, the doctoral student must have fulfilled all first-year requirements in the amount of 60 ECTS, including a confirmed application and an individual research thesis of the second year totalling 50 ECTS.

The Senate may allow the student to progress to a higher year even if he/she has not fulfilled the required conditions in the following circumstances: maternity, prolonged illness, exceptional family or social circumstances, participation in high-profile cultural, sporting or professional events. In this case, the student must provide appropriate evidence.

A student who does not fulfil the requirements for enrolment in a higher year may repeat a year or change to another study programme.

The conditions for completing the study are:

• Successfully completed study obligations prescribed by the programme.
• Publish one (1) scientific article in which the candidate was the first or leading author in journals indexed by SSCI or SCI or SCOPUS with IF>0 or AHCI, namely related to the research field of the doctoral dissertation.
• Participate in any form in one (1) basic/ primary or applicative research project.
• Prepare and successfully defend a doctoral dissertation.

Students enrolled in the Joint Doctoral Program in Computer Science and Data Science acquire the following competencies:

General competences

• The ability to identify a given research problem, its analysis and possible solutions.
• Creating new knowledge that means a relevant contribution to the development of science.
• Ability to master standard methods, procedures and processes of research work at various scientific areas.
• The ability of independent research and development work and management of the research group.
• Knowing the importance of quality and striving for quality of professional work through autonomy, (self) criticism, (self) reflexivity and (self) evaluation.
• Commitment to professional ethics.

Subject-specific competences of compulsory courses

• The ability to solve specific research problems in the field of network analysis.
• Development of skills and abilities in the application of knowledge in the research field of the doctoral dissertation.
• Ability to innovatively use and combine various research methods.
• Skill in identifying research problems that can be formulated as network problems.
• Obtaining scientifically relevant information from a given network.
• Research methods in business sciences.
• The ability to solve concrete research problems in individual fields.
• The ability to use methods important for research in the field of business sciences.
• Development of skills and abilities in the application of knowledge in the research field of the doctoral dissertation.
• Ability to innovatively use and combine various research methods.
• Modeling, analysis and learning from data.
• Ability to solve specific research problems in individual fields.
• Development of skills and abilities in the application of knowledge in the research field of the doctoral dissertation.
• Ability to design and implement original solutions to given scientific problems.
• The ability of a complex systems view and an interdisciplinary approach, which manifests itself as understanding the connection between individual disciplines and sub-disciplines.
• Mastery of a wide range of methodological approaches from the fields of data and computing sciences and the ability to use them.
• Knowing the realistic limitations of the discussed methods and identifying opportunities for improvement.