Intern for master thesis focusing on generative AI for communication systems at Fraunhofer Institute. Engaging in literature review, design, and performance evaluation of AI-based transmission schemes.
Responsibilities
Conduct a comprehensive literature review on generative models applied to physical layer 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 study in the field of communication theory, signal processing, and 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, NumPy, SciPy.
Benefits
Flexible working hours that are perfectly compatible with your studies.
Open and friendly working atmosphere in which your ideas are valued.
Diverse tasks that inspire and challenge you.
Application-oriented research to put your theoretical knowledge to practice.
Exciting and pioneering projects that make a real difference.
Opportunity to write a master's thesis in cooperation with the institute.
Job title
Intern – Gen-AI for Joint Source and Channel Coding of Short Multimedia Packets
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