Advanced Signal Processing & Communications Engineering (MSc)
This Master's programme is part of the Elite Network of Bavaria and has a duration of four semesters. It is taught in English and is aimed at highly qualified students with ambitious career goals.
- The programme is designed for holders of excellent Bachelor's degrees in electrical engineering, computer science, applied mathematics or closely related disciplines.
- Admission is granted to highly talented individuals only. Applicants that are in doubt whether they meet the rigorous admission standards are encouraged to simultaneously apply for other MSc programmes at FAU.
- The programme focuses on fundamental concepts for advanced technologies in the areas of artificial intelligence, signal processing and communications such as information theory, coding, statistical signal processing, machine learning, optimisation and game theory.
- Kick-off Seminar
- Information Theory and Coding
- Statistical Signal Processing
- Machine Learning in Signal Processing
- Mathematical Optimisation in Communications and Signal Processing
- Non-technical elective courses
- Technical lab courses
- Selected topics in ASC
- Applied Game Theory in Information Engineering
- Deep Learning
- Winter School, Summer School
- Technical compulsory elective modules
- Research project (minor) - optional
- Research project (major)
- Technical elective courses
- Technical lab courses
- Master's thesis
- A kick-off seminar right before the winter semester.
- A winter school complements the scientific education with general soft skills and targeted people management and business development skills.
- A summer school prepares students for the research-based training in the second year of the programme.
- The study programme includes three research projects, one of them being the six-month Master's thesis.
- Publication of research results is strongly encouraged and travel costs for conference presentations will be covered.
- Students will be aided by professors in setting up an individualised study programme tailored to their interest and career goals.
- Student jobs for all students are guaranteed to cover part of their cost of living.
- With Germany being one of the most productive industrial economies, engineers are always in high demand. Demographic developments and the ever-growing demand for young graduates familiar with latest technologies lead to plenty of openings with attractive salaries for ASC graduates. Aside from the traditional employers in the communication industry, ASC students can expect to find numerous opportunities in industries whose competitiveness greatly depends on embedded information technology, such as medical technology, energy systems ('smart grids') or the automotive industry. The Nuremberg Metropolitan Region also has many major players in all of these fields.
- The cooperation partnership between FAU and the Fraunhofer IIS ('Home of MP3') makes Erlangen a global leader in audio and multimedia technologies. The university chairs involved within the ASC programme have a wide range of cooperation partners in industry, including Alcatel-Lucent, Audi, BMW, Deutsches HörZentrum Hannover, Dolby Germany GmbH, EADS, Ericsson, Huawei, IAD, Institut für Rundfunktechnik, Intel, NTT, Sennheiser, Shure and Siemens. During their studies, students can complete research projects as part of joint research projects of FAU and industry.
- The ASC Master's degree programme builds on Bachelor's programmes in information and communication technology. It exposes students to cutting-edge research and development in the core areas of communications and multimedia technology and related interdisciplinary topics. The programme structure complies with internationally recognised Master's degree programmes and meets the requirements for qualifying for subsequent doctoral studies. The four-semester curriculum starts in the winter semester and includes a thesis which is written over a six-month period. All modules are taught in English and do not require prior knowledge of the German language.
ASC focuses on interdisciplinary concepts that are fundamental for advanced technologies in the areas of artificial intelligence, signal processing and communications. Besides information theory, coding and statistical signal processing, this includes machine learning, optimisation and game theory. Students deepen the broad interdisciplinary scope of these topics by choosing various areas of specialisation.
Selected faculty members guide the students in composing their own curricula tailored to their individual interests and career goals.The four-semester curriculum starts with a kick-off seminar right before the winter semester. The study programme includes at least two or even three research projects, one of them being the six-month Master's thesis.
A winter school complements the scientific education with general soft and targeted people management and business development skills. A summer school prepares the students for the research-based training in the second year of the programme. Furthermore, students can opt to participate in various events organised by the Elite Network of Bavaria.
- Engineering mathematics: linear algebra, complex analysis, linear differential equations, Fourier transform, Laplace transform, z-transform
- Signals and Systems (textbook, e.g. Oppenheim/Willsky, Signals and Systems)
- Communications (textbook such as Haykin, Communication Systems)
- Stochastic signals (textbook such as Pillai/Papoulis: Probability, Random Variables, and Stochastic Processes)
- Software: MATLAB
The application and the admission procedures are organised in several steps.
For more information: Application
Please find more detailed information on how to apply for a Master or advanced degree programme on the following website: https://master.fau.de.
Degree type: Master of Science (MSc)
Type of study: Master
Standard duration of study: 4 Semester
Start date of degree programme: Winter Term
Admission: Qualification assessment
Early entrance programme: no
Part-time study: no
Faculty: Faculty of Engineering
Elite degree programme: yes