Theoretical Computer Science: Structural theory of automata, composition and decomposition of automata. Tree automata and tree languages, tree transducers. Algebra of languages and tree languages. Term rewriting systems. Multidimensional languages. Automata and semirings, formal power series. Automata and formal logic. Formal semantics. Algebra of concurrent processes. Fixed points in computer science. Iteration theories. Categories in computer science. Grammar systems, formal language models of distributed and cooperative systems. DNA computing, molecular computer science.
Operations Research and Combinatorial Optimization: Theory of economic decision making (multifactor decision making, group decision making). Fuzzy theories. Learning algorithms. Global optimization. Reliable numerical procedures. Optimization in chemical phase-balance tasks. Interval inclusion functions. Process network synthesis. Bin packing algorithms. On-line algorithms. Scheduling problems. Set partitioning. Logistics / Supply planning tasks.
Software Engineering: Advanced programming paradigms. Theory of Compilers. Effective compilation of embedded mobile systems. Legacy system analysis. Software maintenance. Program slicing and its applications. Software reengineering. Object-oriented design and development (C++, JAVA). Web programming (XML). Databases, data mining. Network protocols. Testing of protocols. Formal specification of protocols. Common memory parallel programming. Shared memory parallel programming. Software testing.
Artificial Intelligence: Machine learning algorithms (decision trees, genetic algorithms, neuron networks). Complexity of learning algorithms. Speech recognition. Natural language processing. Frame and rule based knowledge representations. Peer-to-peer networks.
Image Processing: Image reconstruction from projections. Discrete tomography. Medical image analysis. Image segmentation. Image registration and fusion. Computer vision. Skeletonization, thinning and their applications. Discrete geometry and topology.
Electrical and Computer Engineering: FPGA based emulated-digital CNN-UM implementation, FPGA based image and signal processing. Sensors, sensor networks, embedded systems, sensor based signal processing. Robotics, trajectory tracking, pneumatic artificial muscles, fuzzy control. Noise and fluctuations in different systems, applications of secure communication. Software instrumentation.
There are two ways of obtaining the PhD degree: by following a four-year study program, or by individual preparation. The program of which the duration is 4 years prescribes the accomplishment of 240 credits, active participation in the Institute's seminars, and the conduction of research under the supervision of a thesis adviser appointed by the Council of the Doctoral School. At the end of the fourth semester, the completion of 5 courses is included, the courses embrace a number of fields in computer science without the intention of being exhaustive. A course may be offered as a reading course if enrollment is low. In such cases consultation is provided. The language of education in the four-year program is mainly Hungarian, but for foreign students, each course may be offered in English.
The teaching and research staff of the Doctoral School consists mainly of scientists working at the Institute of Informatics and the Research Group on Artificial Intelligence of the Hungarian Academy of Sciences. Some members of the Institute of Mathematics (Faculty of Sciences and Informatics), Department of Medical Physics and Informatics (Faculty of Medicine), and the Department of Applied Informatics (Juhász Gyula Teacher Training College Faculty) also participate in the School. Foreign lecturers may also announce courses in the Doctoral School.
The requirements for obtaining the PhD degree are the following. At the end of the second year, each candidate has to pass a comprehensive doctoral exam which has two main parts. During the first (theoretical) part, the student takes exams in one major subject/topic and in one minor subject/topic. In the second (dissertation) part of the comprehensive exam the student holds a lecture, giving account of his/her knowledge about relevant scientific literature and his/her research results, and describing his/her research plan for the second part of the doctoral training, and the schedule for writing the dissertation and publishing the results. Regarding language skills, a state examination or equivalent at a level not lower than intermediate is required in a foreign language accepted by the School. A lower level examination or equivalent is required in a second foreign language. One of the two languages must be English. Special rules apply to foreign students. As a third major requirement, each applicant has to fulfil the publication requirements of the Doctoral School. As a last major requirement, each candidate has to prepare and defend a doctoral thesis containing new scientific results in computer science, or high-level applications of computer science in other areas. A dominant part of the results included in the thesis has to be published before submission.