Fraunhofer IIS

Intern, Master's Thesis – Gen-AI for Joint Source and Channel Coding of Short Multimedia Packets

Fraunhofer IIS

part-time

Posted on:

Location Type: Hybrid

Location: Erlangen • Germany

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Job Level

Entry Level

Tech Stack

NumpyPythonPyTorchTensorflow

About the role

  • Conduct a comprehensive literature review on generative models applied to the physical layer of communication.
  • Design and implement generative AI–based transmission schemes (e.g., using VAE, GAN, or diffusion models).
  • Evaluate the performance of these schemes against conventional digital baselines in terms of distortion, reliability, and efficiency.

Requirements

  • You are studying in the fields of communication theory, signal processing, or machine learning.
  • Solid understanding of physical layer concepts, including modulation and channel coding.
  • Hands-on experience with Python and machine learning frameworks such as PyTorch or TensorFlow, and with numerical libraries like NumPy and SciPy.
Benefits
  • Flexible working hours that are fully compatible with your studies.
  • Open and friendly working atmosphere where your ideas are valued.
  • Diverse tasks that inspire and challenge you.
  • Application-oriented research and opportunities for practical experience.
  • Attractive possibilities to join the institute on a full-time or part-time basis after graduation.
  • Opportunity to write a master's thesis in cooperation with the institute.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
generative modelstransmission schemesVAEGANdiffusion modelsperformance evaluationmodulationchannel codingPythonmachine learning