Fraunhofer IIS

Intern – Master's Thesis, Generative 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 the application of generative models to the physical layer of communication systems.
  • 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 with respect to distortion, reliability, and efficiency.

Requirements

  • Enrolled in a degree program in communication theory, signal processing, electrical engineering, computer science, or a related field.
  • Solid understanding of physical-layer concepts, including modulation and channel coding.
  • Practical experience with Python and machine learning frameworks such as PyTorch or TensorFlow, and proficiency with NumPy and SciPy.
Benefits
  • Flexible working hours that fit well with your studies.
  • An open and friendly work environment where your ideas are valued.
  • Diverse and stimulating tasks that challenge and inspire you.
  • Application-oriented research opportunities to apply theoretical knowledge.
  • Exciting, pioneering projects that have real-world impact.

Applicant Tracking System Keywords

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

Hard skills
generative modelstransmission schemesVAEGANdiffusion modelsperformance evaluationdistortionreliabilityefficiencymodulation