Questions of examinations for PhD admission
PhD in Mathematics
The simplest Differential equations (5 ECTS);
Probability Theory and Mathematical Statistics (5 ECTS);
Algebraic Structures (5 ECTS);
Functional Analysis or Measurement Theory (5 ECTS).
Total: 20 ECTS
There is no need to study prerequisite subjects if your Master’s degree (major) is a relative specialty.
Upon the successful completion of PhD in Mathematics at SDU, graduates are able to
- Produce, communicate and defend an original contribution to knowledge, as evidenced by the writing and defence of a thesis involving significant original research.
- Communicate mathematical ideas, results, context, and background effectively and professionally in written and oral form.
- Demonstrate advanced knowledge and understanding of their area of specialization
- To create, implement, and disseminate knowledge in mathematics by producing high quality and original research
- Demonstrate abilities in the critical analysis and quantitative reasoning of global problems arising in Mathematics
Objectives of PhD in Mathematics program are to teach students advanced concepts of mathematics, empower them with computational skills to model and solve mathematical problems using computers, and provide opportunity to gain necessary background of their needs.
Specifics/features: PhD in Mathematics Program reflects the active subjects of contemporary mathematics and equips students’ skill sets for the future. It opens new scientific perspectives in the chosen area of specialization.To produce academics with high quality innovative problem-solving skills in their area of expertise
Compulsory & elective modules (courses)
- Real analysis
- Methods of writing PhD thesis
- Implementation of the doctoral dissertation
- Scientific research work of the doctoral student
- Pedagogical practice in Higher Education
- Scientific and research practice
- Formalization and defence of doctoral degree dissertation
- Topics in Real Analysis
- Topics in Algebra
- Topology and Geometry
- Differential Equations
- Partial Differential Equations
- Complex analysis
- Machine learning
- Deep learning
- Data Сollection, Wrangling, Analysis and Visualization
Work as an academic in higher educational institutions
Language of instruction
Dr. Shirali Kadyrov