Research in Computer & Systems Engineering (RCSE)

This English-taught, research-focused Master’s runs over four semesters and is organized into four consecutive phases that build students’ theoretical foundations and research abilities while allowing growing specialization.

In the first phase you take core courses across key areas such as algorithms, information systems, mobile communication networks, software and systems engineering, and control engineering. Research methods and presentation skills are practised through seminars to prepare you for later project work. In the second phase you choose from a wide elective catalogue to gain advanced knowledge in topics including machine learning and deep learning, distributed systems, complex embedded systems, cellular communication systems, system identification and optimisation, systems security and software safety, advanced computer graphics, advanced database systems, and quantum computing.

The third phase emphasizes individual and team research projects where you apply what you’ve learned to current industrial or academic problems; this stage also develops teamwork and presentation skills and may include an optional internship. The programme culminates in a master’s thesis that asks you to address a novel research question, thereby preparing you for careers in research or industry.

Key facts / application notes

• Duration: 4 semesters (full programme structure split into four phases)
• Language of instruction: English
• Programme focus: Research training, advanced electives, project work and a master’s thesis
• Practical options: Individual and team research projects; optional internship during phase 3
• Admissions/details: The original description does not list specific entry requirements or application documents—check the university’s official programme page for exact academic prerequisites, language requirements, application deadlines and visa information.

Curriculum overview

This Master’s program blends traditional teaching with hands-on, research-driven learning. Instruction is delivered through lectures and seminars that build theoretical foundations and expose you to current literature. Practical elements — including laboratory work and collaborative group studies — let you apply algorithms, tools, and measurement techniques to real-world problems in computer and systems engineering. Small-group discussions and seminars encourage critical analysis, debate, and close interaction with faculty and peers.

The programme places strong emphasis on independent research: you will design and execute research projects that synthesize theory and practice, preparing you for a research career or advanced industry roles. By working on project-based assignments and participating in focused seminars and labs, you develop the technical, methodological and communication skills needed to formulate research questions, run experiments or simulations, interpret results, and present findings clearly.

Key modules (types of teaching and learning activities)

• Lectures: core theory, methods, and state-of-the-art topics in computer and systems engineering
• Seminars: focused literature reviews, guest talks, and thematic discussions
• Practical elements: laboratory sessions and structured group study to develop experimental and implementation skills
• Research projects: supervised research work that integrates learning into a substantive investigation
• Small-group discussions: tutorial-style interaction for critique, problem solving, and idea development

Learning outcomes

• Ability to conduct independent research: formulate research questions, design studies, and manage projects
• Practical competence in laboratory and computational methods relevant to systems and computer engineering
• Critical reading and synthesis of scientific literature through seminars and discussions
• Effective scientific communication: writing reports, presenting results, and defending conclusions
• Collaborative and project-management skills developed via group studies and team-based research

Curriculum components (requirements)

• Lectures
• Seminars
• Practice elements (labs, group studies)
• Research projects
• Small-group discussions

Graduates are prepared for research and industry roles that require advanced skills in algorithms, systems engineering, communications and software safety. Typical positions include software/systems engineer, machine learning or data scientist, embedded systems developer, communications engineer and cybersecurity specialist. The programme’s strong research component and master’s thesis also provide a direct pathway to doctoral studies and careers in academic or industrial research.