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Research Assistant

United Arab Emirates University, Department of Family Medicine
Abu Dhabi, UAE
fulltime
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AssistantResearch
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Job Description

The Computer and Network Engineering Department at the United Arab Emirates University is seeking a highly motivated research assistant to join our team focused on developing novel AI-based resource allocation and management techniques for the advancement of AI-empowered wireless networks.

The successful candidate will work in collaboration with other researchers to develop novel radio resource allocation techniques based on emerging AI algorithms for cutting-edge technologies and applications such as cellular networks, UAV-assisted networks, autonomous vehicles, and smart cities.

Responsibilities

  • Design and develop advanced AI-based algorithms and tools to optimize the utilization and allocation of radio resources for future wireless networks.
  • Conduct experiments to validate the performance and functionality of the developed solutions in realistic scenarios.
  • Collaborate with research partners to develop and implement new resource allocation applications for future wireless networks.
  • Publish research findings in high-impact journals and conferences.

Minimum Qualification

  • A minimum of a Master's degree in Electrical Engineering, Computer Science/Engineering, or a related field.
  • Proven knowledge and experience in wireless communications, such as channel models, multi-antenna propagation, etc.
  • Good knowledge of emerging technologies, such as semantic communication, digital twins, metaverse, UAVs, RISs, etc.
  • Expertise in AI algorithms, such as deep reinforcement learning (DRL), multitask DRL, generative models, etc.
  • Deep understanding of multi-dimensional convex and non-convex optimization concepts and state-of-the-art methods and tools used to solve them.
  • Proficiency in programming languages, especially Python, MATLAB, and C++.
  • Excellent written and oral communication skills.

Preferred Qualification

  • Expertise in radio resource allocation and management techniques for wireless systems, especially beyond 5G networks, including hardware and software design.
  • Good knowledge of biologically inspired optimization methods, such as PSO, genetic algorithms, etc.

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