Postdoc in Optical Fibre Sensing using Machine Learning – DTU Electro

Updated: 3 months ago

Applications are invited for a 2-year postdoc position funded by the HORIZON-RIA Software enabled Fiber Optic Multisensing Network (SoFiN) project. The main goal of the project is to realize sensing networks by using the existing fiber infrastructure for both purposes, carrying data and perform sensing. The sensing networks developed within the project will be used for supervision and performance monitoring of complex industrial plants and critical infrastructure, such as electrical power lines, water pipe networks, telecommunication networks and railroad tracks. 

The objective of the proposed project is to develop machine learning based approaches for enhancing the sensitivity of optical fiber sensing networks as well as for processing large amounts of data.  Ideally, one of the objectives of the project is to develop techniques for reaching the ultimate sensitivity limits, which is governed by the laws of quantum mechanics. The project is interdisciplinary and will cover topics within the field of machine learning, fiber-optic communication, information theory and quantum optics. 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 fiber-optic communication and measurements systems, in general. A close collaboration with Friedrich Alexander University of Erlangen, ADVA Optical Networking and NKT Photonics is envisioned within the project

Responsibilities and qualifications
Your work will includes research into machine learning methods for efficient processing of large-amounts of sensor data as well as techniques for enhancing the sensitivity of fiber-optic sensor networks 

Specifically you will focus on the following areas:

  • Various types of autoencoders for dimensionality reduction and feature extraction
  • Generative models for emulation of monitoring events for fiber-optic networks
  • State-space based Bayesian filtering framework for joint tracking of polarization, amplitude and phase noise
  • Bayesian estimation for sensitivity enhancement  
  • Building experimental set-ups for testing the developed machine learning approaches
  • Maintenance  of the GitHub repository for the developed code
  • Organising and managing joint experiments with the collaboration groups

Candidates should have a PhD degree in telecommunication, machine learning, photonics engineering or equivalent. Moreover the candidate shall have experience with one or more of the following skills:

  • Optical or digital communication systems, or fiber based sensing systems
  • Machine learning techniques such as: neural networks, Bayesian filtering, reinforcement learning, evolutionary algorithms, numerical optimization
  • Experimental realization of high-speed optical communication systems or fiber-optic sensing systems
  • Python/PyTorch/TensorFlow/MATLAB
  • Ability to work independently, to plan and carry out complicated tasks
  • Excellent communication skills in English, both written and spoken
  • Innovative skills and the ability to generate new ideas
  • Experience in student supervision at B.Sc., M.Sc. and Ph.D. levels 

Assessment
In the assessment of the candidates, consideration will be given to

  • Publications at leading conferences and journals within the field of optical/digital communication/machine learning
  • Invited conference and journal papers
  • Overall research experience
  • International experience
  • Internal and external collaboration
  • Communication skills

The assessment of the applicants will be made by 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 2 years. The starting date is expected approx. September 2023.

You can read more about career paths at DTU here .

Further information
Further information may be obtained from Senior Researcher Francesco Da Ros (fdro@dtu.dk). 

You can read more about DTU Electro at www.electro.dtu.dk .

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark .

Application procedure
Your complete online application must be submitted no later than 17 March 2023 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • Application with a focus on the “Assessment” bullets points listed above
  • CV
  • Up to three most important publication
  • H-index, and ORCID (see e.g. http://orcid.org/)
  • Diploma (MSc/PhD)

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

Applications 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 Electro has 320 employees with competencies in optics and is one of the largest centers in the world based solely on research in photonics and electronics. Our photonics research is performed within optical sensors, lasers, LEDs, photovoltaics, ultra-high speed optical transmission systems, bio-photonics, nano-optics, and quantum photonics.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,400 students and 5,800 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.


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