Vacancy: PhD or postdoc position - Embedded deep learning

(01-03-2019) Important: this position is available from April 1st and will be filled in as soon as an excellent candidate is found!


IDLab is a research group of UGent, as well as a core research group of imec.  IDLab performs fundamental and applied research on data science and internet technology, and counts over 300 researchers.  Our research areas include machine learning and data mining; semantic intelligence; multimedia processing; distributed intelligence for IoT; cloud and big data infrastructures; wireless and fixed networking; electromagnetics, RF and high-speed circuits and systems.

The AIRO team of IDLab focusus on AI (mostly using neural network techniques) and robotics. In particular, the group has been studying various kinds of neural networks for more than 20 years. It has been at the forefront of deep learning research ever since it became popular a decade ago. Illustrative of this success are an excellent track record at Kaggle competitions and the fact that four of our former PhD students are now working at Google’s Deepmind and one at Google Brain.

The job

Over the last decade, deep learning has seen a trend towards increasing network size and complexity, requiring ever more computing power for both, training and inference. In part, this trend has been reinforced by the same companies that sell GPU cloud services. For example, Google (and Deepmind) has been a driving force behind enabling deep learning through easy-to-use libraries (Tensorflow, Keras) and by demonstrating what can be achieved with massive data and massive computing.

With the rise of IoT there exists a range of tiny electronic sensors that are small enough to be massively integrated in embedded devices, such as wearables, implantables, cars, drones, robots, etc. Systems that involve these embedded sensors often require state-of-the-art deep learning algorithms to perform robust detection, tracking, recognition, etc. However, such sensors possess limited bandwidth, and depending on the application also have latency or privacy requirements. Moreover, power consumption, performance, robustness, accuracy and cost are critical operational objectives for systems relying on sensor input. They therefore require the use of specific embedded hardware and cannot rely on cloud-based solutions. The recently approved icon project cREAtIve aims to take a step back to consider how we can get the best performance out of limited computing resources. The particular focus of this project is on embedded devices for traffic monitoring and automotive applications.

Within the context of cREAtIve, we are urgently looking for an excellent candidate to join our team, either a PhD student or a post-doc. You will find techniques to trade-off between network accuracy and different resource types when targeting implementations on FPGA. You will focus on working within the constraints typically found for industrial applications (real-time operation, power budget, resource cost, installation and maintenance cost) while maintaining the desired accuracy. You will evaluate your work on traffic camera image streams. You will stay up to date with important changes in the related literature. And be encouraged to publish and present your work at international conferences, or to attend useful summer schools.


  • You have a degree in Master of Science/Engineering, preferably in Computer Science, Electronics-ICT or Informatics.     
  • You are interested in and motivated by the research topic, as well as in obtaining a PhD degree. You are specifically interested in combining the fields of hardware design and deep learning.
  • You preferably have experience with machine learning (deep learning) and VHDL-based hardware design.
  • You are efficient and goal-directed. You want to achieve concrete and useful results. Relevant experience in industry is an asset for this project.
  • You have excellent analytical skills, can work independently as well as in team. You have good communication skills.
  • You are a native Dutch speaker or speak and write English fluently (C1 CEFR level).
  • You can start immediately (April first or shortly after)

Additional requirements for PhD student:

  • Note: to be admissible to the PhD-program, your degree must be equivalent to 5 years of engineering studies (bachelor + master) in the European Union, and you must have a solid academic track record (graduation cum laude or grades in the top 25% percentile).
  • You are eligible for a Flemish PhD scholarship (i.e., you have not enjoyed such a scholarship before).

Additional requirements for postdoc:

  • You have a doctoral degree in computer science engineering or electronics engineering (European or ratified as equivalent)

Our offer

The research for this project is fundamental and innovative, but with clear practical applications. You will join a young and enthusiastic team of researchers, post-docs and professors.

For PhD students, we offer a fully funded PhD scholarship for a maximal period of 4 years (upon positive progress evaluation after the first year). For postdocs, we offer a 2 year postdoc position.

This position is available immediately.


Apply with motivation letter, scientific resume, diplomas and detailed academic results (courses and grades), English proficiency scores (for non Dutch speakers), relevant publications, and two reference contacts.

Incomplete applications or applications that are not explicitly targeted at this position will not be considered!

For any questions, contact .

After the first screening, suitable candidates will be invited for an interview (also possible via Skype) and may be asked to pass an assignment for skills assessment.


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