PhD candidate in Computer Science

Faculty of Science – Informatics Institute

19 september 2017
€2,222 to €2,840 gross per month
19 november 2017
38 hours per week

The Faculty of Science holds a leading position internationally and participates in a large number of cooperative programs with universities, research institutes and companies. The faculty has around 6,000 students and 1,600 members of staff in eight research institutes and a diverse set of support services. Many projects are externally funded, either from Dutch and international sources both public and private. Since September 2010, the faculty resides in a new building at the Science Park in Amsterdam, one of the largest centres of academic research in the Netherlands.

The System and Network Engineering (SNE) Lab is one of the three largest research labs at the Informatics Institute (IvI) of the University of Amsterdam (UvA), which has consistently been ranked among the top 100 computer science departments in the world by various international university rankings. The SNE Lab conducts research on leading-edge computer systems of all scales, ranging from global-scale systems and networks to embedded devices. Across these multiple scales our particular interest is on extra-functional properties of computer systems, such as performance, energy consumption, reliability, programmability, productivity, trustability, and security.

The SNE Lab invites applications for a fully funded PhD candidate position in the area of embedded systems design for deep learning applications. More specifically, the PhD candidate will be involved in the research project 'software framework for runtime-Adaptive and secure deep Learning On Heterogeneous Architectures' (ALOHA), which is funded by the EU Horizon 2020 program.

Project description

Deep Learning (DL) algorithms are an extremely promising instrument in artificial intelligence, achieving very high performance in numerous recognition, identification, and classification tasks. To foster their pervasive adoption in a vast scope of new applications and markets, a step forward is needed towards the implementation of the on-line classification task (called inference) on low-power embedded systems, enabling a shift to the edge computing paradigm. Nevertheless, when DL is moved at the edge, severe performance requirements must coexist with tight constraints in terms of power/energy consumption, posing the need for parallel and energy-efficient heterogeneous computing platforms. Unfortunately, programming for this kind of architectures requires advanced skills and significant effort, also considering that DL algorithms are designed to improve precision, without considering the limitations of the device that will execute the inference. The main goal of the ALOHA project is to facilitate implementation of DL on heterogeneous low-energy computing platforms.

To this aim, the project will develop a software development tool flow, automating:

  • algorithm design and analysis;
  • porting of the inference tasks to heterogeneous embedded architectures, with optimized mapping and scheduling;
  • implementation of middleware and primitives controlling the target platform, to optimize power and energy savings.

During the development of the ALOHA tool flow, several main features will be addressed, such as architecture-awareness (the features of the embedded architecture will be considered starting from the algorithm design), adaptivity, security, productivity, and extensibility. ALOHA will be assessed over three different use-cases, involving surveillance, smart industry automation, and medical application domains.

The PhD candidate is expected to:

  • perform research in the scope of the ALOHA project, with a focus on modeling, simulation and optimization techniques for designing embedded DL applications;
  • complete and defend a PhD thesis within the official appointment duration of four years;
  • collaborate with other SNE/IvI researchers as well as with researchers from the project consortium;
  • regularly present intermediate research results at international conferences and workshops, and publish them in proceedings and journals;
  • assist in relevant teaching activities.


  • M.Sc in computer science or computer engineering;
  • preferably some prior expertise in one or more of the following fields: embedded systems, computer architecture, modeling and simulation, and AI/deep learning; 

  • fluency in oral and written English is required as well as good presentation skills;
  • strong programming skills in C/C++;
  • able to work in a research team.

Further information

Further information can be obtained from:


The appointment will be full-time (38 hours a week) for a period of four 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 for the PhD candidate. The PhD candidate is also expected to assist in teaching of undergraduate students.

The salary is in accordance with the university regulations for academic personnel. The salary will range from €2,222 (first year) up to a maximum of €2,840 (last year) before tax per month (scale P) based on a full-time appointment. 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 good benefits;
  • top-50 University worldwide;
  • one of the best deep learning ecosystems in the world;
  • interactive, open-minded and a very international city;
  • excellent computing facilities.

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

Please apply using the link below. Applications must include:

  • a letter of motivation explaining why you are the right candidate;
  • curriculum vitae (including a link to your MS Thesis);
  • a complete record of BA/MS courses including grades;
  • a list of projects you have worked on (with brief descriptions of your contributions, max 2 pages) and any publications.

You will also need to provide contact details for 2 referees. They will be contacted directly.

The committee does not guarantee that late or incomplete applications will be considered.

The selection process will consist of multiple rounds, during which (selected) candidates may also be asked to complete a programming challenge.

Applications will be accepted until 19 November 2017. #LI-DNP

No agencies please

Gepubliceerd door  Universiteit van Amsterdam