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  3. PhD position: Low-Power Neural Network Based Object Classification and Tracking for Video and Radar

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PhD position: Low-Power Neural Network Based Object Classification and Tracking for Video and Radar

The PhD student’s research activities will include: Define efficient ways for data-collection and training of neural networks using a combination of video and …

4 maanden geleden

Arbeidsvoorwaarden

Standplaats:
Drienerlolaan, Enschede, Overijssel
Dienstverband:
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 - 38 uur
Salarisindicatie:
€ 2266 - € 2897 per maand
Opleidingsniveau:
WO

Functieomschrijving

The PhD student’s research activities will include:

  • Define efficient ways for data-collection and training of neural networks using a combination of video and radar data.
  • Define power-efficiency optimized neural network hardware implementations for classification of radar and video images. The objective is to improve the power-efficiency by algorithm-hardware co-design.
  • Design and implement a demonstrator on FPGA using an automotive radar and a camera.

We are looking for a creative and inventive researcher who has a proven affinity with research.

The ZERO program is funded by NWO. The program consists of a number of projects that focus on power-efficient digital HW design at different levels of abstraction. This PhD position is part of the Autonomous Roadside Monitoring (ARM) project in the ZERO program. Partners of this project are the University of Eindhoven, and the companies NXP-semiconductors, Topic and Vinotion.

The project will be carried out in the Chair CAES which is part of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). The Dependability research of the chair is part of the multidisciplinary Centre for Telematics and Information Technology (CTIT, www.ctit.utwente.nl/), the largest research institute of the university. More information on the Chair can be found on caes.cs.utwente.nl/.

Functie-eisen

We are looking for highly motivated researchers with an MSc degree in Embedded Systems, Computer Science, or Electrical Engineering with excellent experimental and theoretical skills. Knowledge and/or experience with hardware/software/algorithm design of deep neural networks is desirable, preferably you studied at another University in Europe. You are able to work independently as well as in a project team, and you have good communicative skills. Fluency in English speech and writing is a basic requirement.

INFORMATION AND APPLICATION

To apply for the position you should follow the link at the bottom of this vacancy description. Your application should consist of:

  • a cover letter (maximum 1 page A4), emphasizing your specific interest, qualifications and motivations to apply for this position;
  • a full Curriculum Vitae, including a list of all courses attended and grades obtained;
  • a short description (maximum 1 page A4) of your MSc research;
  • contact details of at least two referees who worked closely with you
  • a document proving fluency in English, if it is not your native language;
  • a fully completed application form, which can be downloaded from the UT vacancy site;
  • Since only three documents can be uploaded per application, please combine documents if needed. Only complete applications submitted by the deadline will be taken into consideration.

Applications should be submitted before Saturday December 15th, 2018.

For more information about the position you can contact Prof.dr.ir M.J.G. Bekooij (m.j.g.bekooij@utwente.nl)

Arbeidsvoorwaarden

We offer a very challenging fulltime position for four years in an inspiring multidisciplinary and international environment. In accordance with the Collective Labour Agreement for Dutch Universities(CAO NU) the gross monthly salary ranges from € 2266,- in the first year to € 2897,- in the fourth year. Additionally, the University of Twente provides excellent facilities for professional and personal development, a holiday allowance and an-end-of-year bonus, and a number of additional benefits. Your main responsibility will be to carry out research, but you will be given the opportunity to acquire some teaching experience as well.