2 PhD positions on Data-Efficient Deep Learning for Video Surveillance 

Faculty of Science – Informatics Institute

Publication date
17 October 2018
Level of education
Master's degree
Salary indication
€2,266 to €2,897 gross per month
Closing date
1 December 2018
Hours
38 hours per week
Vacancy number
18-628

The Informatics Institute (IvI) of the Faculty of Science invites applications for 2 PhD candidates on Data-Efficient Deep Learning for Video Surveillance, for a period of four years. The positions are part of the Dutch Efficient Deep Learning program. You will be based in the Intelligent Sensory Information Systems Lab led by Prof. Cees Snoek within the Informatics Institute. You will also cooperate with Prof. Henry Bal in the High Performance Distributed Computing group at Vrije Universiteit Amsterdam. Furthermore, you will spend part of your time at either Royal Schiphol Group or TNO.

Project description

Deep learning has advanced video understanding significantly, especially when striving to recognize simple concepts like cats or boats in mainstream video content. When the footage is more sensitive or specialized, like video from surveillance cameras or self-driving cars, and semantics of interest are more demanding, like actions involving people and their interactions, deep learning solutions suffer from their limited ability in learning multimodal and temporal-aware video representations, especially when labeled examples are scarce. To address these challenges, we are looking for two PhD candidates on data-efficient action recognition and multimodal person-re-identification. The candidates will be part of the Efficient Deep Learning program conducted in close collaboration with industry. The results of these PhD projects will be validated at Amsterdam Schiphol Airport and TNO (partners of the project). The use cases involve automating the manual monitoring of streaming surveillance cameras for events involving people and their activities.

The following PhD positions are available for you to choose from:

  1. The PhD candidate on data-efficient action recognition will be supervised by Prof. Cees Snoek, and will work part-time at Schiphol;
  2. The PhD candidate on multimodal person-re-identification will be supervised by Prof. Cees Snoek and dr. Gertjan Burghouts (TNO), and will work part-time at TNO.

The Efficient Deep Learning (EDL) program combines the fields of machine learning and computing. Both disciplines are strongly represented in the Netherlands and are now connected by seven Dutch academic institutes and more than 35 other (industrial) partners in- and outside the Netherlands. The EDL program contains seven use-case driven EDL research projects: P1) Deep Learning as a service, P2) Reconstruction, matching and recognition, P3) Video analyses and surveillance, P4) High tech systems and materials, P5) Human and animal health, P6) Mobile robotics, and P7) Deep Learning platforms. The common goal for all seven EDL projects is to significantly improve the applicability of Deep Learning among others by creating data efficient training, and improving computational efficiency, both for training and inference.

Requirements

  • Master's degree in Artificial Intelligence, Computer Science, or related field;
  • preferably with a specialization in computer vision and/or machine learning;
  • excellent programming skills (the project is in Python and C/C++);
  • solid mathematics foundations, especially statistics and linear algebra;
  • highly motivated;
  • fluent in English, both written and spoken.

Further information

For informal inquiries on the positions please contact :

Appointment

Preferred starting date: between January 2019 and March 2019.

The appointment will be full-time (38 hours per week) on a temporary basis for a period of 4 years (initial employment is 18 months). Periodic evaluations will be held after 9 and 14 months, and upon positive evaluation, the appointment will be extended to a total of 48 months. The appointment must lead to a dissertation (PhD thesis). An educational plan that includes attendance of courses, summer and/or winter schools, and national and international meetings will be drafted. We also expect you to assist in teaching of undergraduate students.

The salary is in accordance with the university regulations for academic personnel and will range from €2.266 (first year) up to a maximum of €2.897 (last year) before tax per month (scale P). There are also secondary benefits, such as 8% holiday allowance per year and the end of year allowance of 8.3%. The Collective Labour Agreement for Dutch Universities is applicable.

Some of the things we have to offer:

  • competitive pay and excellent benefits;
  • top-50 University worldwide;
  • one of the best AI ecosystems in the world;
  • excellent computing facilities.
  • interactive, open-minded and a very international city;

English is the working language in the Informatics Institute. As in Amsterdam almost everybody speaks and understands English, candidates need not be afraid of the language barrier.

Job application

The UvA is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We value a spirit of enquiry and endurance, provide the space to keep asking questions and cherish a diverse atmosphere of curiosity and creativity.

You may only submit your application by electronic mail using the link below. We will accept applications until 1 December 2018. To process your application immediately, please quote vacancy number 18-628. The committee does not guarantee that late or incomplete applications will be considered. Please do not send or copy your application to Cees Snoek. We will consider only applications via the online process.

In your application you should clearly indicate which of the two PhD positions it is that you are applying for.

Your application must include:

  • a motivation letter explaining why you are the right candidate;
  • curriculum vitae, (max 3 pages);
  • a link to your Master’s thesis;
  • a complete record of Bachelor and Master courses (including grades);
  • a list of projects you have worked on (with brief descriptions of your contributions, max 2 pages);
  • the names and contact addresses of at least two academic references.

All these items should be grouped in a single PDF attachment. #LI-DNP

No agencies please

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