PhD in Informatics and Computational Science

• Advanced Signal Processing Methods
• Applets of Integral and Discrete Transforms
• Applied Functional Analysis
• Applied Linear Algebra
• Basic Methods of Statistical Data Analysis in Practice
• Bio-Inspired Computing
• Classical and Quantum Methods of Molecular Simulations
• Code Analysis and Optimization
• Computational Electrical Engineering
• Computer Security
• Data Analysis
• Data Compression
• Digital Image Processing
• Discrete Mathematics
• Graph Theory I
• HPC libraries and tools
• Image Analysis
• Information Retrieval Systems
• Introduction to Quantum Chemistry with Applications
• Machine Learning
• Mathematical Methods and Tools for Reliability and Risk Analysis
• Mathematical Modelling and FEM
• Methods of Optimization
• Modeling and Simulation of Complex Systems
• Modelling in Electrical Power Engineering
• Modelling of Mass and Heat Transfer
• Numerical Methods
• Parallel Algorithms
• Parallel Architectures
• Petri Nets
• Physical Implementation of Database Systems
• Query Processing in Database Systems
• Reliability of Electronic Devices
• Selected Problems of Fluid Mechanics
• Social Networking
• Software Defined Radio
• Theory of Computation
• Theory of Formal Systems
• Transparent Intensional Logic
• Variational Methods for Engineers
• English Language Dr
• French Language Dr
• German Language Dr
• Spanish Language Dr.

Study aims

The PhD programme aims to train highly qualified experts capable of further developing their field by finding new original solutions, methods and procedures, as well as capable of applying the most demanding known methods in new areas. Graduates are typically employed in research and development and higher education. It is also typical to work internationally, for example, participating in international teams and defending results to the international community, participating in the research departments of multinational companies or as independent consultants. The programme aims to draw on the links between the Faculty of Electrical Engineering and Computer Science and the IT4Innovations Research Centre, which is involved in the programme, to ensure that students have maximum research opportunities and access to world-class knowledge and computing infrastructure.

Graduate's knowledge

The graduate has a professional overview across the entire field of Computer Science and other involved areas, in the breadth and depth beyond the level of a graduate student. Theoretical knowledge of the core disciplines (e.g. mathematics, discrete mathematics, theoretical computer science) is deepened in ways that are directly applicable to applied and basic research in the chosen subfield. The graduate has a deep theoretical and practical knowledge especially in the specific chosen subfield according to the focus of their research work. Understands scientific methods used in the field of his/her specialization and can apply them himself/herself. Typically, the knowledge of graduates covers computer science and mathematics, as well as one or more application areas such as industrial digitisation, supercomputing, but also chemistry or biology.

Graduate's skills

The graduate can design new, effective and well-theoretically justified solutions based on original ideas that are accepted by the international scientific and professional community in the field. He/she can implement, evaluate and compare even very complicated existing procedures. Can solve interdisciplinary problems, requiring knowledge not only from computer science and mathematics but also from a collaborating discipline (e.g. biology and medicine, engineering, economics, etc.). Can anticipate directions of development in his/her field. He can also implement very large and complex works, usually as the leader of a research team. He or she can choose the appropriate solutions procedures and appropriate technologies, based on the use of the latest knowledge. He can independently develop extensive technical texts in a foreign language, especially English, presenting even very complicated and abstract ideas. He/she can defend the proposed solutions in a professional discussion at the international level.

Graduate's general competence

Graduates can use the scientific approach to problem-solving, set goals, determine strategies, choose theoretical backgrounds, choose alternative solutions, communicate with people in problem-solving, e.g. manage the work of a team of researchers, present and defend their views and chosen solution methods in a foreign language in an international forum, communicate with top experts in the field in a foreign language, especially in English, popularize their field, influence developments in their field, take responsibility for their decisions and the work of their team, and take into account the social impact of the decisions they make.

Hard skills

• Explorative analysis
• CUDA
• Deep learning
• Parallel programming
• PyTorch
• Mathematical methods and analyses
• Programming techniques (C, Java…)
• Regression analysis
• Methods of complex network analysis
• Optimization methods
• Statistical data analysis
• Algorithms and data structures
• Work with data (big data)
• Mathematics - knowledge of arithmetic, algebra, geometry, calculus, statistics and their applications.
• Data analysis
• MPI

Graduate's employment

During their studies, graduates absorb the maximum amount of knowledge within their chosen field of study. Their knowledge gives them the basis for solving the most complex problems in research and development activities in large companies, universities or institutes of the Academy of Sciences. Thanks to their experience of studying literature in a foreign language and their ability to assimilate this knowledge, they can apply it in their work. In addition, they can defend their views, even in international forums, and can participate fully in research and multinational companies.

Therefore, the graduates can be employed within the development teams of companies to solve the most complex tasks, as leaders of research teams, and researchers in industry and academia. Examples of employers include Microsoft, Avast, ABSA, Google, SAP, Siemens, CGI, and others.

Professions

• Mathematician
• Developer of image analysis systems
• Research team worker
• Consultant
• Data analyst (specialist)
• Data analyst
• Research and development specialist
• System Architect
• Researcher
• Specialist in science, research and development
• Data scientist
• Analyst
• Developer industry 4.0 application
• HPC specialist
• Data scientist
• Computer programmer - specialist