PhD Researcher in AI/ML for Intelligent Optical Network Management

3 weeks ago


Gothenburg, Västra Götaland, Sweden Chalmers tekniska högskola Full time

Job Summary

Chalmers tekniska högskola is seeking a highly motivated PhD researcher to join our team in the field of Artificial Intelligence and Machine Learning (AI/ML) for Intelligent Optical Network Management. The successful candidate will have the opportunity to work on cutting-edge research projects, collaborating with industry leaders and academia.

About the Project

The PhD project aims to leverage AI/ML techniques to address key challenges in optical network design and operation. The researcher will work on developing and integrating proof-of-concept demonstrators, addressing different technological readiness levels, from simulation to deployment. The project will focus on applying AI/ML to optimize optical network design, network flexibility and reliability, advanced monitoring, and failure management.

About the Division and Unit

The (CAOS) division conducts advanced research on various aspects of communication infrastructure, including network automation, control and management, fiber access and mobile transport networks, network sustainability, reliability, security, and survivability, and converged fiber-wireless networks.

Major Responsibilities

  • Independently formulate research questions and develop strategies to solve them, within the scope of the project.
  • Develop new AI/ML approaches for optimizing optical network design and operation, and integrate them into proof-of-concept demonstrators.
  • Work collaboratively with other forward-thinking team members and external researchers from academia and industry.
  • Communicate the results of your research (verbally and in writing) in high-impact journals and conferences.

Requirements

The ideal candidate will have a strong background in AI/ML, optical networking, or a related field, with excellent research and communication skills. The ability to work independently and collaboratively in a team environment is essential.



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