Senior Researcher - AI for Networking

Key Skills

Aartificial intelligence, Deep Learning, Effective communication skills, Machine learning techniques, NeurIPS, PyTorch, Reinforcement Learning, TensorFlow

Job Description

Our team has an immediate permanent opening for a Senior Researcher.

Responsibilities:

• Contributing to the synthesis of new approaches/designs to improve the performance of the next generation telecommunication systems
• Proposing and developing advanced AI/ML models to address the real-world issues of communications and networking
• Proposing and developing advanced learning paradigms to support deep learning in the 5G/6G era
• Communicating with business units to find out their challenges, and solving them with AI/ML tools
• Translating mathematical problem definitions and model/solution specifications into efficient executable code
• Conducting experiments on large-scale data sets to verify and evaluate the proposed ideas and solutions
• Keeping track of the latest progresses in the (selected) AI/ML areas (especially federated learning, distributed learning, transfer learning, knowledge distillation, and or complex-valued neural networks), as well as telecommunications
• Proposing high-impact intellectual properties (e.g., patents);Publishing or contributing to the publishing of research papers in top-tier AI/ML and communications/networking venues
• Generating organized technical reports
• Working closely with the team, as well as other Huawei units (if needed)

Job requirements

What you'll bring to the team:

• A Ph.D. degree in Computer Science, Electrical and Computer Engineering, Communications, Statistics, Applied Mathematics, or a related field; or a master degree with 5+ years of work experience in the related fields
• Preferably 2+ years of work experience in AI/ML or telecommunications
• Good understanding of Deep Learning (DL) components (e.g., regularization, generalization and batch normalization), and DL paradigms (e.g., supervised/unsupervised learning, reinforcement learning, representation learning)
• Publications in high-quality AI/ML venues (e.g., NeurIPS, ICML, ICLR, AAAI) and/or top communications/networking venues (e.g., SIGCOMM, INFOCOM, NSDI, ToN, JSAC, TWC)
• Strong AI/ML coding skills; experienced with Tensorflow or Pytorch
• Research experience on AI/ML for telecommunication and networking is an asset
• Project experience in federated learning, distributed learning, transfer learning, knowledge distillation, and/or complex-valued neural networks is an asset
• Good communication skills, willingness to collaborate, self-motivated