Data and AI Governance Specialist supporting clients with data/AI governance structures and practices. Leading governance workstreams, developing key artifacts, and establishing ongoing monitoring approaches.
FI
Hybrid Intern – Master’s Thesis: Generative AI for Joint Source and Channel Coding of Short Multimedia Packets
Posted last month
About the role
- Intern/Master Thesis focusing on generative AI for multimedia communication at Fraunhofer Institute. Engage in cutting-edge research on machine learning and communication engineering in a collaborative environment.
Responsibilities
- Conduct a comprehensive literature review on generative models applied to the physical-layer of communication.
- Design and implement generative AI–based transmission schemes.
- 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.
- You have a 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, as well as NumPy and SciPy.
Benefits
- Flexible working hours compatible with your studies.
- Open and friendly working atmosphere.
- Diverse and inspiring tasks that challenge you.
- Opportunities to continue with the institute in a full-time or part-time role after graduation.
- Opportunity to write your master’s thesis in collaboration with the institute.
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