XR Networking & ML Researcher (Wi‑Fi Focus)

Universitat Pompeu Fabra - Department / School of Engineering; España; On-site; EUR 27,000 - 33,000; Full time

Job summary

Universitat Pompeu Fabra - Department / School of Engineering in Barcelona seeks a Research Assistant to design and evaluate AI/ML-based solutions for Wi‑Fi networks supporting XR applications such as VR and AR. The role focuses on learning to select and configure protocols to meet throughput, latency and reliability requirements while optimizing spectrum use.

The work covers XR systems over Wi‑Fi, machine learning integration, and evaluation using simulations and experiments.

Qualifications

• Bachelor’s and Master’s degree in Engineering in areas related to networks or artificial intelligence.
• Extensive knowledge of wireless networks, especially Wi‑Fi.
• Advanced programming skills in Matlab, Python and/or C.
• Experience in using simulation/experimentation for research in networks and communications.
• Proven experience in performance evaluation, analysis, simulation and experimentation.

Responsibilities

• Study the state of the art in wireless networks, XR networking and ML.
• Develop, implement and evaluate networking functionalities for XR over Wi‑Fi.
• Develop ML algorithms to improve operation of network functionalities.
• Contribute to writing research deliverables and publications.

Skills

Wireless networks knowledge

Artificial intelligence

Machine learning

Programming in Matlab

Python

C

Experience in simulation

Performance evaluation

English proficiency

Education

Engineering degree in networks / telecommunications / CS

Master's degree in related area

Tools

Matlab

Python

C

Job description

Universitat Pompeu Fabra - Department / School of Engineering in Barcelona seeks a Research Assistant to design and evaluate AI/ML-based solutions for Wi‑Fi networks supporting XR applications such as VR and AR. The role focuses on learning to select and configure protocols to meet throughput, latency and reliability requirements while optimizing spectrum use.

The work covers XR systems over Wi‑Fi, machine learning integration, and evaluation using simulations and experiments.