Ribbon Israel are looking for a MSc / PhD, Doctoral Student for AI Project to join our system research team in Israel.

Responsibilities

• Research of Optical layer Network Digital Twin, combining Optical Hardware and Software AI/ML algorithms
• Performing Simulation of Optical phenomena, modeling of optical behavior, using ML algorithms
• Participating in system architecture and requirements definition for the network Digital Twin-based implementation
• Participating in development and integration efforts, while providing answers to complex Optical system issues, arising from the digital twin activity
• Position is for hybrid work (with mandatory 2 days per week to visit office)
  
  

Key Challenges

• Selecting the models for the digital twin (statistical or a deterministic model)
• Optimal incorporation of measurements uncertainty into the digital twin model
• Use of the digital twin to give information regarding network operation and behavior
• Changing practices regarding the design and operation of optical networks based on a data driven, probabilistic based approach, rather than the established margin-based approach
  
  

Requirements

• Optics MSc/PhD student/researcher in the area of Optical networks and Optical phenomena research
• Proven background and academia experience in Optical communication field research. Advantage - Machine Learning algorithms research
• Proven programming experience in MATLAB/Python
• Must have MSc or PhD course in Optical Communication. Advantage – Course in Machine learning
• Strong analytical skills, ability to see the whole picture and integrate different disciplines into a single, coherent picture
• Ability to simplify complicated problems while complying to the system requirements
• Registered student in an Israeli university, faculties of Physics/Optics/Electrical engineering
• Located in Israel
  
  

Position is for hybrid work (with mandatory 2 days per week to visit office)

Please Note:

'All qualified applicants will receive consideration for employment without regard to race, age, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, on the basis of disability, or other characteristic protected by applicable law.'