The intern will support research activities at the intersection of AI/ML and advanced wireless communication systems, with a particular focus on AI-native air interfaces for 6G or Reconfigurable Intelligent Surfaces (RISs).
While AI/ML techniques are already being studied in 3GPP for physical layer enhancements (e.g., beam management, positioning, CSI), 6G envisions an air interface where AI is deeply integrated into the transceiver chain.
This internship will investigate AI-driven approaches for online adaptability, RIS-assisted connectivity, and autonomous channel estimation, targeting applications such as vehicular communications.
Wireless Communication Fundamentals:
1.
Basic understanding of digital communications (concepts like signals, noise, and bandwidth).
2.
Interest in learning about OFDM, modulation, coding, and MIMO (prior coursework is helpful but not required).
Software & Tools:
1.
Exposure to MATLAB/Simulink.
2.
Basic Python programming skills (NumPy/SciPy; familiarity with AI/ML frameworks like TensorFlow or PyTorch is a plus, but not mandatory).
3.
Curiosity about simulation platforms such as ns-3 / LENA (optional).
Additional Competencies:
1.
Willingness to tackle analytical and problem-solving tasks with guidance.
2.
Ability to read and summarize technical content (standards or papers) at a high level.
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