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    Master thesis on deterministic AI inference on-board Telecom Satellites - Munich, Deutschland - airbus

    airbus
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    Ganztags
    Beschreibung

    Job Description:

    In order to support our team, Airbus Defence and Space is looking for a

    Masterand student in the field of deterministic AI inference on-board Telecom Satellites (d/f/m)

    Are you up to discover and inspire advanced processing solutions using Artificial Intelligence on high-end FPGA-based hardware for next-generation Telecom Satellites? Do you want work at the edge of innovation in this field? Then apply now

    • Location: Ottobrunn/Munich
    • Start: June or July 2024
    • Duration: 6 months

    You will support the department Telecom & Navigation Processing Germany which specializes in high performance processing solutions for satellites. The R&T focus is satellite on-board machine learning inference and application design for radio frequency (RF) communication, anomaly detection, network orchestration, as well as future 5G/6G payloads.

    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.

    Your tasks and responsibilities

    Artificial Intelligence offers great potential in aeronautics and space, such as computer-vision guided aircraft navigation and landing maneuvers, or self-supervising spacecrafts that autonomously recover from faults. Besides high accuracy requirements on neural networks for such critical applications, the on-board inference must be performed in a predictable and time-deterministic manner to satisfy flight certification requirements.

    Airbus has developed a custom in-house AI inference engine which is now ready to be integrated into spacecraft hardware. Your tasks will focus on deploying this engine on our next-generation FPGA-based System-on-Chip (SoC) spacecraft processor system. This includes:

    • Implementing the in-house IP-core on the spacecraft's FPGA
    • Ensuring efficient data streaming to/from the IP by implementing high-speed interfaces
    • Extending the AI capabilities by integrating new layers/operations
    • Comparing of key metrics (power efficiency, data throughput, compute power) to other state-of-the-art space-grade ML accelerators

    With this position you will have the opportunity to work in an interdisciplinary team of AI specialists across the Airbus divisions and shape the AI-capabilities of future satellite systems.

    Desired skills and qualifications

    • Enrolled full-time student within a background in VHDL Engineering, Electrical Engineering, Artificial Intelligence, or similar field of study
    • Experience with industry-standard FPGA tools, such as Vivado
    • FPGA and embedded-systems programming skills (VHDL / Verilog, Python, C, C++)
    • Experience with common Machine Learning frameworks (Tensorflow / PyTorch / Matlab)
    • Fluent English is mandatory; French or German would be an asset

    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 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:

    Final-year Thesis

    -------

    Experience Level:

    Student

    Job Family:

    Support to Management


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