PhD for On-board Machine Learning Applications for Telecommunication Satellites in 5G/6G Non-Terrestrial Networks (d/f/m)

Job description

Job Description:

Are you up to discover and inspire advanced solutions for future 5G-6G Telecom Satellites? Do you want to be part of the group of leading experts in this field?

We look forward to you joining us as a PhD student (d/f/m) within Airbus Defence and Space, Telecom & Navigation Processing Germany – TSTCG for 35 hours/week, (flexi-time).

Location: Ottobrunn/Munich
Start: as soon as possible
Duration: 3 years

You will support the department Telecom & Navigation Processing Germany which specializes in high performance processing solutions for satellites. The R&T focus are satellite on-board future 5G/6G payloads as well as artificial intelligence support.

Your location
Our site is just a stone's throw away from Munich, the beautiful capital of Bavaria. Are you into sports and other outdoor activities? The Alps and Lake Starnberg are within an hour’s reach, offering a multitude of recreational options.

Your benefits

· 
Attractive salary and work-life balance with an 35-hour week (flexitime).

· 
International environment with the opportunity to network globally.

· 
Work with modern/diversified technologies.

· 
At Airbus, we see you as a valuable team member and you are not hired to brew coffee, instead you are in close contact with the interfaces and are part of our weekly team meetings.

· 
Opportunity to participate in the Generation Airbus Community to expand your own network.

Scope of PhD thesis

Autonomous spacecraft would be a major game changer in the satellite industry, and future Telecommunication Satellites are envisioned to be either carrying more complex payloads or deployed in huge constellations. Hence, on-board AI applications are present on the roadmap for Non-Terrestrial Networks (NTN), where satellites will become a part of future 5G/6G networks. They are seen as possible “data centers in space” where processing can be offloaded. Therefore, autonomous operation of on-board processing is becoming crucial for communication enhancement, network orchestration, anomaly detection, and remote sensing analysis. All in all, the goal to achieve is edge AI inference, with high reliability and low system requirements.

The PhD position will support the on-going R&D activities on on-board Machine Learning applications for 5G/6G NTN. The candidate shall research one or more of the following topics (but not limited to), with a focus on their embedded implementation:

· 
Channel estimation and equalization

· 
Radio resources management and network optimization

· 
Beamforming

· 
Traffic transmission

· 
Adaptive link coding & modulation

· 
Constellation cognitive intelligence

· 
Network slicing

Qualifications

· 
Master Degree in Telecommunication Engineering, Electrical Engineering or similar field of study

· 
Basic knowledge of communication standards (CCSDS, 3GPP, 5G)

· 
Good signal processing background

· 
Embedded programming skills (C, C++, VHDL)

· 
Scripting skills (Matlab, Python)

· 
Proven experience with Tensorflow, Pytorch, and/or other Neural Network modeling frameworks

· 
Experience of Neural Networks Inference on embedded processing platforms (CPU, FPGA) is a plus

· 
Experience on using cloud services (AWS) is a plus

· 
Interest in spacecraft and new trends in telecommunications

· 
Fluent English is mandatory; German would be an asset

· 
Dynamic, proactive, organized with focus on delivery

· 
Good team player, have excellent communication skills, and are able to work independently

Please upload the following documents: cover letter, CV, relevant transcripts, enrollment certificate. 
Not a 100% match? No worries! Airbus supports your personal growth.

Take your career to a new level and apply online now!

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company:
Airbus Defence and Space GmbH

Employment Type:
PHD, Research

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Experience Level:
Student

Job Family:
Computing&Comm and Info& Data Processing

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