Get a PhD scholarship in Machine Learning and Optical Communication at Denmark Technical University (DTU) 2020

DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Applications are invited for a 3-year PhD position funded by the European Commission’s ERC consolidator grant: ‘FRECOM – Nonlinear-Distortion Free Communication over the Optical Fibre Channel’. The objective of the FRECOM project is to develop novel machine learning based strategies for communication over the nonlinear optical fiber channel. The start date is flexible, but preferably before December 1, 2020.

The project is interdisciplinary and will cover topics within the field of machine learning and optical communication. The project will be carried out in Machine Learning in Photonic Systems (M-LiPS), group. The group has a strong track record and industry collaboration in the application of machine learning techniques to optical communication systems and photonic systems in general.

This Ph.D. project will explore the latest advances within machine learning to enable nonlinear-distortion free communication over the optical fibre channel. It will be explored how to combine machine techniques with Nonlinear Fourier Transform (NFT), to enable spectrally efficient and robust optical communication systems covering ultra-wide band transmission (O+E+S+C+L band). More specifically, the application and efficient training for auto-encoders will be investigated. The project will cover both algorithm development as well as experimental implementations.

Responsibilities and tasks:
This PhD position will investigate the research topics below using both theoretical and experimental methods, but not limited to these topics:
• Develop novel machine learning based transmitter and receiver schemes for conventional as well as nonlinear Fourier division multiplexing systems
• Investigate the impact of non-ideal transmission schemes on the performance of nonlinear signalling schemes
• Apply machine learning algorithms to improve the knowledge on the transfer function applied by the nonlinear fiber channel

Opportunity Focus Areas:
Photonics engineering ( Fiber-Optic System)