Master Thesis in Error Correction for Binary Neural Networks in Noisy Hardware and Space Environment Job Details

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Master Thesis in Error Correction for Binary Neural Networks in Noisy Hardware and Space Environment

Job Description

Req ID: 5366

Place of work: Oberpfaffenhofen

Starting date: as soon as possible

Career level: Student research project and final thesis

Type of employment: Full-time, Part time

Duration of contract: 6 months

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 12,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!

The DLR Institute of Communications and Navigation is dedicated to mission-oriented research in selected areas of communications and navigation. Its work ranges from the theoretical foundations to the demonstration of new procedures and systems in a real environment and is embedded in DLR's Space, Aeronautics, Transport, Security and Digitalization programmes.

What to expect

The Information Transmission Group was established within the Satellite Networks Department of the Institute of Communications and Navigation to investigate techniques for reliable and secure transmission, processing and storage of information. Grounded on a firm theoretical background, we target the development of algorithms for satellite and (more generally) for wireless communication systems, with emphasis on forward error correction schemes, physical layer techniques and (massive) multiple access. Specific application areas of interest are currently satellite/cellular IoT systems, high-throughput wireless links (including free-space optical communications), as well as high-mobility channels and reliable processing and storage of information.

Your tasks

investigation of coding-theoretic methods to increase the robustness of binary neural networks implemented on noisy hardware platforms, such as memristor crossbars or radiation-prone memories used in space applications
research involves the analytical modeling of the noisy hardware environment
implementation and evaluation of various decoding strategies (e.g., Belief Propagation, Approximate Message Passing, and hard-decision decoders)
exploring the trade-offs between decoding complexity and robustness

Your profile

Solid background in digital communications, information, and coding theory.
Fundamental understanding of neural networks.
Advance programming skills.
Excellent academic records.

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 5366) please contact:

Dr. Federico Clazzer
Tel.: +49 (0) 8153 281120