We are looking for a highly motivated and skilled engineer who is willing to deepen his/her knowledge in AI-related techniques such as deep learning and reinforcement learning applied to wireless communication networks.
The successful candidate will participate in the experimental research activities of the R&D project 6G AI-Native Air Interface (6G-AINA), a three-year project which follows up on the successful predecessor project ARISTIDES (https://aristides.cttc.es/).
The 6G-AINA project aims to contribute algorithmic innovations towards accomplishing a truly AI-native air interface for 6G communication systems. Specifically, AI/ML algorithms will help improve beamforming with NOMA and rate-splitting, extend current proposals of deep learning based coded modulation and waveform designs, as well as enhance the accuracy, sustainability and bandwidth efficiency of extremely large antenna arrays and cell-free massive MIMO networks.
Experimental activities will be based on software defined radio (SDR) modules. The selected candidate is expected to develop demonstrators and an experimental platform based on USRPs to test AI-based communication algorithms under realistic channel conditions. The offered position is an excellent opportunity to further develop the candidate’s SDR skills, acquire state-of-the-art experience on wireless communication networks demonstrators, as well as cutting-edge knowledge on machine learning/AI-related techniques for PHY layer communication systems.
For more information about the 6G-AINA project, visit https://www.cttc.cat/project/6g-ai-native-air-interface/. This contract and the 6G-AINA project are supported by grant PID2021-128373OB-I00, PRE2019-089309 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe
Closes: 02/09/2024
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