PhD student on Scalable Video Analysis on low-power GPU architectures

Where: Eindhoven

 

The Electronic Systems Group of the Department of Electrical Engineering at Eindhoven University of Technology (TU/e) invites applications for a PhD position on Computer Vision Deep Learning Algorithms and Architectures.

Project description

Since the introduction of deep learning (DL) techniques, the advances in video analytics are going in a rapid pace. Deep learning is based on neural networks comprising multiple layers of connected neurons that can be trained to classify input signals. In the domain of video analysis, this technique is used to detect, analyze, recognize, or classify objects. The deep neural network requires a tremendous amount of compute power and huge memory bandwidth. To satisfy these requirements advanced DL algorithms and architectures have to be developed which exploit parallel processing, in particular vector parallelism, specific accelerators, and advanced memory interfaces and memory hierarchy.

Within the ZERO program for Energy Autonomous Systems for Internet of Things, the PhD student will research techniques to efficiently map deep neural networks to various low energy consuming heterogeneous hardware and processing platforms, including GPUs, FPGAs and ASICs. The driver application, a smart surveillance camera system, will be delivered by one of the partners in the project (ViNotion, www.vinotion.nl).

Location

The research will be carried out in the Electronic Systems Group of Eindhoven University of Technology and in the research lab of ViNotion, also in Eindhoven. The Electronic Systems (ES) group consists of seven full professors, one associate professor, nine assistant professors, several postdocs, about 40 PDEng and PhD candidates and support staff. The ES group is world-renowned for its design automation and embedded systems research. ViNotion is a leading company in the smart surveillance area.

ViNotion

ViNotion is an innovative development company for computer vision applications, focusing on software development. The company has 10-15 employees, of which most have a master or PhD degree in advanced signal processing. For its R&D, ViNotion works closely together with the Eindhoven University of Technology that is located 3 km from the office.
ViNotion offers products and services for crowd analysis and traffic analysis with intelligent video camera systems. The products and services can not only count but are also able to distinguish pedestrians, bicycles and a multitude of different vehicle types, measure speed, density and GPS positions, among others. These products are being applied for city marketing, retail footfall, crowd and event management, train stations, mobility reporting, urban planning, traffic control, tolling, etc. As a service, ViNotion provides mobility services and offers crowd and traffic analysis systems.

Job requirements

The ideal candidate is pro-active, highly motivated, and independent, and has proven experience with the design of embedded systems. The candidate has also good written and oral communication skills in English. We are looking for candidates that match the following profile:

  • A master degree in Computer Science, Electrical Engineering or related disciplines with excellent grades.
  • Excellent knowledge of computer architectures.
  • Very good algorithmic skills, in particular with respect to vision and deep learning.
  • Very good programming skills (e.g., in C or C++) on CPUs and GPUs.
  • Experience with hardware design (e.g., in Verilog or HLS) and FPGAs.
  • A team player that enjoys working in multicultural teams.
  • Good communication and organization skills.
  • Excellent English language skills (writing and presenting).

Information and application
For more specific information about these positions please contact: prof. dr. Henk Corporaal (H.Corporaal [at] tue.nl), dr. ir. Sander Stuijk (S.Stuijk [at] tue.nl)

If interested, please use ‘apply now’-button at the top of this page. You should upload the following:

  • Detailed curriculum vitae, a letter of motivation and portfolio with relevant work;
  • Cover letter explaining your motivation and suitability for the position;
  • Detailed Curriculum Vitae (including a list of publications and key achievements in research project(s));
  • Contact information of two references;
  • Copies of diplomas with course grades;

Candidates will be selected based on graduation mark and proficiency at university including consideration of the reputation of the university, relevant experience and skills, writing skills and publications, work experience as well as performance in relevant modeling exercises and interviews.

Please keep in mind; you can upload only 5 documents up to 2 MB each.

Applications can be send to info <AT> vinotion <DOT> nl.

 

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