AI Fellows Program at Anthropic fostering research and engineering talent. Engaging in empirical AI projects with mentorship and resources.
FI
Hybrid Intern – Gen-AI for Joint Source and Channel Coding of Short Multimedia Packets
Posted last month
About the role
- 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
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
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