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  3. PhD candidate in Embedded Systems Design for Distributed Deep Learning

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PhD candidate in Embedded Systems Design for Distributed Deep Learning

The Parallel Computing Systems (PCS) group at the Informatics Institute (IvI) of the University of Amsterdam and the Leiden Embedded …

7 maanden geleden


Spui, Amsterdam, Noord-Holland
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 uur
€ 2325 - € 2972 per maand


The Parallel Computing Systems (PCS) group at the Informatics Institute (IvI) of the University of Amsterdam and the Leiden Embedded Research Center (LERC) at the Leiden Institute of Advanced Computer Science (LIACS) of Leiden University are looking for a joint PhD candidate in the area of embedded systems design for deep learning applications.

Deep Learning (DL) algorithms are an extremely promising instrument in artificial intelligence, achieving very high performance in numerous recognition, identification, and classification tasks. Even though DL has gained significant importance, it is still very challenging to implement these algorithms on resource-constrained embedded devices, thereby preventing their pervasive adoption in a vast scope of new Internet of Things (IoT) applications and markets. Thus, a step forward is needed towards implementation of the on-line execution of DL algorithms (called inference) in a distributed manner on several resource-constrained embedded devices in order to enable a shift to the edge computing paradigm which is an integral part of the IoT concept. More specifically, when DL is moved at the edge of IoT, severe performance requirements must coexist with tight constraints in terms of power/energy consumption, available processing and memory resources on small embedded devices (sensor nodes, microcontrollers, small single-board computers like ODROID and Raspberry Pi, etc.), posing the need for a distributed and heterogeneous computing platform interconnecting several of these small embedded devices. Unfortunately, designing DL algorithms such that they can be executed on this kind of distributed platforms would require advanced skills and significant manual effort, also considering that DL algorithms are primarily designed to improve only precision, without considering the aforementioned limitations of the devices that will execute the inference and the communication costs due to data exchange among the interconnected devices. The research of the PhD candidate will therefore focus on methods and techniques for automated analysis and design of distributed DL algorithms when targeting efficient implementation of their inference tasks on the aforementioned type of distributed platforms.

The PhD candidate is expected to:

  • perform research on analysis, modeling, and optimization techniques for designing embedded and distributed DL algorithms;
  • complete and defend a PhD thesis within the official appointment duration of four years;
  • collaborate with other PCS and LERC researchers;
  • regularly present intermediate research results at international conferences and workshops, and publish them in proceedings and journals;
  • assist in relevant teaching activities at IvI and LIACS.


  • M.Sc. in computer science or computer engineering;
  • prior expertise in embedded systems design and AI/deep learning;
  • preferably some expertise in (distributed) computer architectures, and modelling and simulation;
  • fluency in oral and written English is required as well as good presentation skills;
  • strong analytical as well as programming skills (C/C++, Python, Shell scripting, etc.).

 The candidate should be able to work in a research team.


The PhD candidate will be formally appointed at the University of Amsterdam. The appointment will be on a temporary basis for a period of 4 years (initial appointment will be for a period of 18 months and after satisfactory evaluation it can be extended for a total duration of 4 years) and should lead to a dissertation (PhD thesis). An educational plan will be drafted that includes attendance of courses and (international) meetings. The PhD student is also expected to assist in teaching of undergraduates.

Based on a full-time appointment (38 hours per week) the gross monthly salary will range from €2,325 in the first year to €2,972 in the last year. The annual salary will be increased by 8% holiday allowance and 8,3% end-of-year bonus. A favorable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement (Cao) of Dutch Universities is applicable.

Additional information

Further information maybe obtained from:

  • Dr Andy D. Pimentel, Informatics Institute, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands
    T: +31 (0)20 525 7578 
    You may also want to visit his personal website.
  • Dr Todor Stefanov, Leiden Embedded Research Center, Leiden Institute of Advanced Computer Science, Leiden University, Niels Bohrweg 1, 2333 CA Leiden, The Netherlands
    T: +31 (0)71-527 5776
    You may also want to visit his personal website.

The Faculty of Science has a student body of around 6,500, as well as 1,600 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.


Do you recognize yourself in the job profile? Then we look forward to receiving your CV and cover letter by 20 September 2019. You can apply online by using this link.

Applications should include, in a single PDF file:

  • letter of motivation;
  • curriculum vitae (experience recognizable in months);
  • BSc + MSc diploma with transcripts (courses + grades);
  • master’s thesis and other publications (or links referring to);
  • names and contact details of two references;
  • any other relevant material (publications, link to your GitHub repository, …).

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