Phd: Deep Learning For Long Term Video Understanding
Delft University of Technology Faculty Electrical Engineering, Mathematics and Computer Science

Phd: Deep Learning For Long Term Video Understanding


Department/faculty: Faculty Electrical Engineering, Mathematics and Computer Science

Level: University Graduate

Working hours: 38-40 hours weekly

Contract: 4 years

Salary: 2325 - 2972 euros monthly (full-time basis)

Closing date

    May 31, 2019


Faculty Electrical Engineering, Mathematics and Computer Science



The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) is known worldwide for its high academic quality and the social relevance of its research programmes. The faculty’s excellent facilities accentuate its international position in teaching and research. Within this interdisciplinary and international setting the faculty employs more than 1100 employees, including about 400 graduate students and about 2100 students. Together they work on a broad range of technical innovations in the fields of sustainable energy, telecommunications, microelectronics, embedded systems, computer and software engineering, interactive multimedia and applied mathematics.


The Department of Intelligent Systems is part of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at Delft University of Technology. The faculty offers an internationally competitive interdisciplinary setting for its 500 employees, 350 PhD students and 1700 undergraduates. Together they work on a broad range of technical innovations in the fields of sustainable energy, quantum engineering, microelectronics, intelligent systems, software technology, and applied mathematics.


The Pattern Recognition and BioInformatics Group is one of five groups in the department, consisting of seven faculty members and over 20 post-doc and PhD students. Within this group, research is carried out in three core subjects: pattern recognition, computer vision, and bioinformatics. One of the main focuses of the group is on developing tools and theories, and gaining knowledge and understanding applicable to a broad range of general problems, but typically involving sensory data, e.g. time signals, images, video streams, or other physical measurement data.   


Job description


Automatic long term understanding of video is relevant for medical, surveillance, sport applications. Most current work in deep learning focuses on short video snippets. This project is about long-term dependencies in video. The PhD position is shared with TU-Delft and TNO.    




We are looking for students who have recently completed or expect to complete very soon an MSc or equivalent degree in computer science, electrical/electronic engineering, applied mathematics, applied physics, or a related discipline. Experience in some or all of the following or related fields are preferred: Deep learning, Machine Learning, Computer Vision.


The successful applicants will have:

   • good programming skills;


   • Proven experience in DL frameworks;

   • curiosity and analytical skills;

   • motivation to meet deadlines;

   • an affinity for the relevant social science research;

   • good spoken and written communication skills;

   • an interest in communicating their research results to a wider audience;

   • proficiency in English.




Conditions of employment


TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.


As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit for more information.


Information and application


For information about this vacancy, you can contact Dr. J.C. van Gemert, Head of the Computer Vision Lab, email:, tel: +31 15 2788434.


For information about the selection procedure, please contact Karin Reijenga, HR Advisor, email:


To apply, please e-mail a detailed CV along with a letter of application before May 31, 2019 to When applying for this position, please refer to vacancy number EWI2018-72





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