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PhD scholarship in Numerical Framework for All-Optical Reservoir Computing

Danmarks Tekniske Universitet (DTU)

Virksom - a-kasse og faglig organisation for selvstændige

Frist 31. maj 2020

The Machine Learning in Photonic Systems group at DTU Fotonik seeks a candidate for a PhD project on numerically investigating all-optical hardware implementations of reservoir computing. The 3-year PhD position is funded by the Villum Foundation through the Villum Young Investigator Programme: ‘OPTIC-AI – Optical processing unit for high-speed AI applications’.

Current digital implementation of machine learning algorithms are limited in speed and energy consumption by the electronics hardware platform they are implemented on. Moving towards all-optical implementations can overcome these challenges. Therefore the key objective of the OPTIC-AI project is to develop a new optical processing unit for implementing reservoir computing, and machine learning in general, on a photonic hardware platform.

This Ph.D. project will be hosted within the OPTIC-AI team, part of the Machine Learning in Photonic Systems group at DTU Fotonik.

Within the OPTIC-AI team, you will explore the modeling of optical components and relate dynamics of optical systems to the required properties of effective reservoirs to be used for computation. Whereas the focus of the project will be prevalently numerical, it will receive input and feedback from the optical components design and experimental characterization. The project will start by focusing on current demonstrations of optoelectronics reservoir computing and extreme machine learning to subsequently move into fully optical implementations.

Responsibilities and tasks
Your overall responsibility will be to use both theoretical and numerical methods to address some of (but not limited to) the research topics listed below:

  • Investigate machine learning implementations on photonic hardware
  • Investigate the relations between optical nonlinearities and nonlinear dynamics theoretically required by computationally effective reservoirs
  • Develop a numerical framework for simulating photonics components
  • Develop methods to provide all-optical training through linear regression.
  • Analyze achievable energy efficiency and speed for all-optical reservoirs
  • Optimization of optical reservoirs to be fabricated on integrated optical platforms.
  • Investigate the benefit of photonic reservoir computing for optical communication applications, e.g. equalization, classification, end-to-end learning

In general, you are expected to:

  • Develop numerical simulation code in Matlab/Python
  • Construct numerical models of optical and photonic components
  • Propose complex networks of photonic components to implement photonic reservoirs.
  • Analyze the performance of the proposed structures using conventional benchmarking tests (channel equalization, image classification, pattern recognition)
  • Collaborate with other PhD students focusing on the design and characterization of the proposed structures

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 numerical modeling of physical problems and scientific programming (Matlab/Python/Octave/R), as well as a strong background in either machine learning or optics and photonics.

Additionally, the candidates are expected to have passed advanced courses in at least one of the two topics, to have good communication skills in English (both written and spoken) and a proven ability to work independently, to plan and carry out complicated tasks.

The candidates are expected to describe their previous experience with numerical simulations in the cover letter (see below).

Moreover, the following skills will receive additional consideration:

  • Experience with software for version control such as git
  • Theoretical understanding of extreme learning machine and/or reservoir computing
  • Theoretical understanding of nonlinear optics
  • Experience with numerical implementations of machine learning algorithms
  • Experience with machine learning frameworks such as Tensorflow and Pythorc
  • 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 Researcher Francesco Da Ros.

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 will be based at DTU Fotonik, Department of Photonics Engineering, at the Kgs. Lyngby Campus.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Researcher Francesco Da Ros, fdro@fotonik.dtu.dk.

You can read more about DTU Fotonik on www.fotonik.dtu.dk/english.

Please submit your online application no later than 31 May 2020 (23:59 local time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • 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. In a typical year, DTU Fotonik educates 55 PhD students from more than 25 countries and our student numbers are constantly growing. As one of Europe’s largest public photonics research departments, DTU Fotonik covers a multitude of optical disciplines ranging from fundamental light-matter interaction and optical telecommunications to applied research and innovation. Our research topics include 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 vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 11,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland.

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Danmarks Tekniske Universitet (DTU) - hurtigt overblik

Danmarks Tekniske Universitet (DTU)
Danmarks Tekniske Universitet (DTU)
DTU er et teknisk eliteuniversitet med international rækkevidde og standard. Vores mission er at udvikle og nyttiggøre naturvidenskab og teknisk videnskab til gavn for samfundet. 11.200 studerende uddanner sig her til fremtiden, og 6.000 medarbejdere har hver dag fokus på uddannelse, forskning, myndighedsrådgivning og innovation, som bidrager til øget vækst og velfærd.

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