This international, research-oriented MSc programme at TU Ilmenau provides intensive preparation for careers in research and development at global companies and for further academic study. It is presented as an AI engineering programme built around core expertise in communications and signal processing, taught in English and aimed at students who want to combine machine-learning methods with domain-specific signal and communication knowledge.
Coursework and research emphasize foundational topics such as information theory, coding and modulation, optimisation techniques, compressed sensing, tensor-based signal processing, multi‑modal data fusion, machine learning and data analytics, parameter estimation, array signal processing and adaptive filtering. Teaching spans the full protocol stack—from physical-layer radio propagation and hardware/algorithm design to protocols and application-layer systems—and addresses practical challenges through assignments and research projects.
Students carry out supervised research projects in close collaboration with professors and research staff, developing project planning, literature review, teamwork, presentation and scientific-writing skills. Projects are expected to produce documented results and often culminate in conference presentations and journal publications; successful students regularly have opportunities to present at leading international conferences. Graduates are well placed for roles in future wireless systems, autonomous and connected vehicles, radar/sonar, audio and multimedia systems, biomedical signal processing and other industries that apply big-data and AI techniques.
Key facts & application notes
This four-semester MSc curriculum builds a deep foundation in signal processing, communications theory and RF engineering in the first year, then moves into applied, networked and mobile communications plus hands-on research and specialization in the second and third semesters, culminating in an independent master's thesis in the fourth semester. Core technical modules—such as Advanced Digital Signal Processing, Information Theory and Coding, Microwave Engineering, Communications Engineering and Communication Networks—give you strong theoretical and algorithmic skills for analysing and designing modern communication systems. Early exposure to Antenna Engineering and Mobile Communications prepares you for RF design and wireless system implementation.
From semester two onward, the program offers project-based learning (a research project and an advanced research project) and a suite of technical electives that let you focus on topics like multirate signal processing, video and audio coding, deep learning methods for signal applications, multimedia standards, radar signal processing and radio/ cellular standards. Third-semester courses such as Adaptive and Array Signal Processing and Systems Optimisation extend your ability to design robust sensor and communication arrays and to optimise real-world systems. The final semester is dedicated to a written and supervised master's thesis, demonstrating independent research competence and subject-matter specialization.
The curriculum also integrates non-technical "key competency" electives (for example language courses) to strengthen transferable skills and international employability. Elective modules are offered in specified semesters, enabling a tailored path toward careers in telecommunications, multimedia systems, radar and remote sensing, audio/video coding industries, or further academic research.
Requirements (semester-by-semester overview and key options)
You must hold a completed Bachelor's degree of at least six semesters / 180 CP in electrical engineering, information technology, media technology, or a closely related program. Applicants should already have a solid foundation in core topics from the communications and signal-processing area; these are expected prior to starting the Master's program.
Specifically, basic knowledge is required in a number of mathematical and engineering subjects (see list below), and you should be comfortable with basic scientific programming. For programming, experience with Matlab/Octave or Python is expected, including fundamental constructs and array handling. Additionally, applicants whose native language is German are recommended to have completed one semester abroad before the start of the Master's program.
Winter Semester (International)
15 May 2026
Winter Semester (EU/EEA)
15 September 2026
Graduates are prepared for research and development positions in international companies as well as for postgraduate (PhD) studies. Typical roles include communications and signal processing engineer, R&D engineer, systems designer, antenna/radar engineer, biomedical signal processing specialist, and data/AI engineer in sectors such as telecommunications, automotive (connected/autonomous vehicles), medical imaging and healthcare, multimedia and audio technology, defence, and finance. The programme's strong research orientation and opportunities to publish and present work strengthen competitiveness for both industry R&D roles and academic careers.
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