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Advanced Signal Processing & Communications Engineering (MSc)

What is ASC?

A 4-semester Elite Master's programme within the "Elitenetzwerk Bayern" (Elite Network of Bavaria) taught in English for highly qualified students that aim for higher career goals.

  • 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 tough admission standards are encouraged to simultaneously apply to other MSc programmes of FAU.
  • Focusing on fundamental concepts for advanced technologies in the areas of signal processing and communications such as: information theory, coding, and statistical signal processing, machine learning, optimization, and game theory.
Modules and degree programme structure
1st semester
  • Mathematical optimization in Communications and Signal Processing
  • Information Theory and Coding
  • Statistical Signal Processing
  • Game Theory withApplication to Information Engineering
  • Kick-off Seminar
  • Technical Mandatory Elective Courses
  • Technical Lab Courses

2nd semester

  • Machine Learning in Signal Processing
  • Selected Topics in ASC
  • Winter School, Summer School
  • Technical Lab Courses
  • Nontechnical Elective Courses
  • Technical Mandatory Elective Courses

3rd semester:

  • Research Project (Minor)
  • Research Project (Major)
  • Technical Elective Courses

4th semester:

  • Master's thesis
What is different about ASC?
  • A kick-off seminar right before the winter semester
  • A winter school complements the scientific education with soft-skills, in general, and people management and business development, in particular.
  • A summer school prepares the students for the research-based training in the 2nd year of the programme.
  • The study programme includes three research projects, one of them being the six-month master 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 individualized study program tailored to their interest and career goals.
  • Student jobs for all students are guaranteed to cover their cost of living.
For prospective students
  • 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 those industries whose competitiveness greatly depends on the embedded information technology, such as medical technology, energy systems (‘smart grids’), or automotive industry – and the metropolitan area including Erlangen-Nürnberg has many big players in all these fields.
  • The co-operation of FAU and the Fraunhofer IIS (“Home of MP3“) makes Erlangen a world-wide leader in audio and multimedia technologies. The university chairs involved within the ASC program have a wide range of cooperation partners in industry like Alcatel-Lucent, Audi, BMW, Deutsches HörZentrum Hannover, Dolby Germany GmbH, EADS, Ericsson, Huawei, IAD, Institut für Rundfunktechnik, Intel, NTT, Sennheiser, Shure, Siemens, etc. During their studies students can complete research projects within common research projects of FAU and industry.
  • The ASC master study program is based on bachelor and diploma programs with focus on information and communication technology and leads the students to cutting-edge research and development in the core areas of communications and multimedia technology and related interdisciplinary topics. The program structure complies with internationally recognized master programs and meets the requirements for subsequent doctoral studies. The four-semester curriculum starts in winter and includes a six-months thesis project. All courses are taught in English and do not require prior knowledge in German language.
Study program/Curriculum

ASC focuses on interdisciplinary concepts that are fundamental for advanced technologies in the areas of signal processing and communications. Besides information theory, coding, and statistical signal processing, these are machine learning, optimization, and game theory. Students deepen the broad interdisciplinary scope of these topics choosing various areas of specialization.
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 program includes three research projects, one of them being the six-month master thesis.
A winter school complements the scientific education with soft-skills, in general, and people management and business development, in particular. A summer school prepares the students for the research-based training in the 2nd year of the program. Furthermore, students can opt for participation in various events organized by the Elitenetzwerk Bayern.

Pre-requisites
  • Engineering math: 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, e.g., Haykin, Communication Systems)
  • Stochastic Signals (textbook, e.g., Pillai/Papoulis: Probability, Random Variables, and Stochastic Processes)
  • Software: C/C++, MATLAB
Application and admission

The application and the admission procedure are organized in several steps.
Find more information: http://asc.studium.fau.de/for-prospective-students/application.shtml

Studiengangvergleich

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Studiengang-Bild

Abschluss: Master of Science (MSc)
Studienart: Master
Standort: Erlangen
Regelstudienzeit: 4 Semester
Studienbeginn: Wintersemester
Sprache: Englisch
Frühstudium: nein
Teilzeitstudium: nein
Fakultät: Technische Fakultät
Elitestudiengang: ja

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