Digital Transformation & AI Specialist designing digital solutions for a global flower industry company. Enhancing operational efficiency and supporting technological evolution through AI and automation processes.
FI
Hybrid Intern – Master Thesis, Gen-AI for Joint Source and Channel Coding of Short Multimedia Packets
Posted last month
About the role
- Intern working on Master thesis in Generative AI for physical layer communication at Fraunhofer-Gesellschaft. Engage in cutting-edge R&D in Erlangen, Germany.
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.
- You have a solid understanding of physical layer concepts, including modulation and channel coding.
- You have 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 and put your theoretical knowledge to practice.
- Exciting and pioneering projects that make a real difference.
Job title
Job type
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Degree requirement
No Education Requirement
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