PhD scholarship in Performance Prediction of Optical Communication Systems using Machine Learning

DTU Fotonik
Monday 07 Jan 19

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Applications are invited for a 3 year PhD position funded by the European Commission’s Horizon 2020 Marie Skłodowska-Curie Innovative Training Network (ITN): ‘WON – Wideband Optical Networks’. The successful applicant will work at DTU Fotonik in the Machine Learning in Photonic Systems group.

is a doctoral-level training network funded by the European Commission under Horizon 2020 Marie Sklodowska-Curie ITN Action. The program will train 14 early-stage researchers (ESRs) in the area of wideband optical networks through collaboration of academic and industrial highly qualified institutions. Solutions identified within WON will enable to overcome a possible traffic-crunch by achieving a 10-fold increase in the usable optical bandwidth of single- mode fibres. WON will train 14 ESRs in three main areas: a) network management and control plane algorithms; b) design, prototyping and test of transceiver and in-line components; and c) digital signal processing and machine learning techniques and system modelling.

Being highly multidisciplinary, WON will cover all topics and expertise from design and development of photonic components, novel digital signal processing and machine learning algorithms and system modelling to network and control management. WON is a doctoral-level training network that will benefit of rich interactions between the academia and industry. ESRs will benefit from a comprehensive training program featuring inter-sectorial and multidisciplinary technical courses, rich transferable skills training and international inter-sectorial secondments with a strong focus on industrial experience. WON ESRs will be capable of leading interdisciplinary research activities with unique expertise on designing physical-layer-aware wideband optical communication networks. In this context, the WON training networks will serve as a European platform for outstanding doctoral training in the field of ultra-high capacity next generation optical networks.

Project description
Due to the different transmission properties across the entire bandwidth and complex interaction of multiple system parameters such as input signal power, number of channels, link type, modulation format, symbol rate, and channel spacing, the prediction of optical communication system performance is a challenging task. In this project, a data-driven approach using a machine learning and artificial intelligence techniques such as Deep Learning and Gaussian processes is proposed for performance prediction of WDM optical communication systems operating across the entire wavelength range from O- to L-band. The investigated models will be developed to complement the physical-layer analytical model for further optimization and in-service network control. The aim is to explore the techniques from machine learning and artificial intelligence to optimize the performance across the entire spectrum in terms of: reach, information rate and energy efficiency.

Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. Candidates are expected to have experience with the design of advanced modulation formats and digital receivers for optical communication systems and coherent optical communication systems in general. Moreover the candidate shall have additional skills as: 

  • Experience with digital communication
  • Experience using MATLAB or similar
  • Ability to work independently, to plan and carry out complicated tasks
  • Good communication skills in English, both written and spoken
  • Innovative skills and the ability to generate new ideas
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide.  

The assessment of the applicants will be made by Associate Professor Darko Zibar.

We offer
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.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

You can read more about
career paths at DTU here.  

Further information 
Further information may be obtained from Associate Professor Darko Zibar, phone: +45 6146 4688,

You can read more about Department of Photonics Engineering on  

Please submit your online application no later than 15 February 2019 (local time)To apply, please open the link "Apply online", fill out the online application form. The following must be attached in English: 
  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)
Candidates may apply prior to obtaining their master's degree but cannot begin before having received it.

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Fotonik has 220 employees with competences in optics and is one of the largest centers in the world based solely on research in photonics. Research is performed within optical sensors, lasers, LEDs, photovoltaics, ultra-high speed optical transmission systems, bio-photonics, nano-optics and quantum photonics.

DTU is a technical university providing internationally leading research, education, innovation and
scientific advice. Our staff of 6,000 advance science and technology to create innovative solutions that meet the demands of society, and our 11,200 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government and public agencies.