Postdoc in Machine Learning

onsdag 15 dec 21

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Frist 1. marts 2022
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Are you interested in developing new machine learning methods and putting your skills into practice?

If you have a PhD or similar research background in machine learning, and you are looking for the right place to make the most of your knowledge and talent, this is the position for you. As part of the project "Machine learning-enabled fiber-optic communication", you will develop your skills at the forefront of scientific research in machine learning.

In a ground breaking collaboration between researchers in machine learning and photonics, we want to use machine learning to design new fiber-optic communication strategies that are optimized in terms of throughput and energy-efficiency. Your role will be to develop neural network-based machine learning methods for improving communication strategies over nonlinear fiber optic channels, and collaborate on implementing them in our experimental test bed. This could include using convolutional neural networks for pulse shaping at the transmitter and symbol detection at the receiver. With a physical communication channel "in the loop" we envision that gradient-free optimization will play an important role in your research. Depending on your interests, you could approach this using Monte Carlo gradient estimation, active learning, surrogate optimization, or perhaps evolutionary computation.   

As our new colleague, you will be part of a dedicated interdisciplinary research team. You will be based within the Section for Cognitive Systems, which is a lively and research oriented group of scientists and support staff with a broad interest in machine learning and information processing in humans and computers. On a day-to-day basis you will collaborate closely with one other postdoctoral researcher employed in the project as well as the two professors, Mikkel N. Schmidt and Darko Zibar, who lead the project.

We believe that the best scientific results are achieved based on trust in the individual backed by an environment of collaboration, knowledge sharing, and support. You will have considerable freedom to pursue your own ideas as you see fit, and we encourage you to publish your results in the leading machine learning venues.

Responsibilities and qualifications
Your overall focus will be to develop, design, and implement new machine learning methods for optimal digital communication. Your responsibilities will include:

  • Developing ideas for using machine learning to optimize communication strategies.
  • Designing and implementing neural networks for optical communication.
  • Collaborating with practitioners on implementation in our experimental test bed.
  • Communicating your results in machine learning conferences and journals.

We expect that you bring expertise within:

  • Machine learning methods research.
  • Programming in Python and Pytorch / Tensorflow.
  • Creative problem solving and generation of new ideas.
  • Communication in English, both written and spoken.

It is an added benefit if you have experience or interest in the following related topics, but if not we can provide the necessary training:

  • Digital communication systems
  • Digital signal processing
  • Probabilistic modeling

As a formal qualification, you must hold a PhD degree (or equivalent).

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 terms of employment
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. Starting date is as soon as possible according to mutual agreement.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Mikkel N. Schmidt, /

You can read more about DTU Compute at

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 1 March 2022 (Danish 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:

  • Application (cover letter)
  • CV
  • Academic Diplomas (MSc/PhD)
  • List of publications

Applications received after the deadline will not be considered.

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

Working at DTU Compute
DTU Compute is a unique and internationally recognized academic department that spans the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard, and have a long-term involvement in applied and interdisciplinary research in data science, artificial intelligence, and machine learning.

We believe that our strong commitment to diversity, equity, and inclusion helps us attract the most talented individuals and allows the best ideas to flourish. The university itself is located in the greater Copenhagen area, which is acknowledged for its excellent standards of living, childcare, and welfare system. We emphasize a healthy work / life balance based on the premise that you do the best work when you are happy.

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 12,900 students and 6,000 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.