Voor de beste ervaring schakelt u JavaScript in en gebruikt u een moderne browser!
EN

PhD candidate in Embedded Systems Design for Distributed Deep Learning

Faculty of Science – Informatics Institute

PhD candidate in Embedded Systems Design for Distributed Deep Learning
Publicatiedatum 27 mei 2019
Sluitingsdatum 30 juni 2019
Opleidingsniveau Master's degree
Functieomvang 38 hours per week
Salarisindicatie €2,325 to €2,972 gross per month
Vacaturenummer 19-331

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.
The PCS group, headed by Dr Andy Pimentel, performs research on the design, programming and run-time management of multi-core and multi-processor (embedded) computer systems. The modeling, analysis and optimization of the extra-functional aspects of these systems, such as performance, power/energy consumption but also the degree of productivity to design and program these systems, play a pivotal role in this work. The main mission of LERC, headed by Dr Todor Stefanov, is to provide highly innovative contributions to the system-level design of embedded and cyber-physical systems and software – conceptually (theory), methodologically (design methods and tools), and structurally (platforms/architectures). To this end, LERC investigates fundamental methods and model-based techniques for the specification, analysis, development, programming, verification, and implementation of Embedded (Cyber-Physical) Systems-on-Chip (SoC).
The aim is to work towards a joint doctorate degree from both the University of Amsterdam and Leiden University. This means that the PhD candidate will be jointly supervised by Dr Pimentel and Dr Stefanov and is expected to spend roughly half of his/her working time at either location (Amsterdam and Leiden).

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. 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.

Requirements

  • M.Sc. in computer science or computer engineering;
  • preferably some prior expertise in one or more of the following fields: embedded systems and design, (distributed) computer architectures, modelling and simulation, and AI/deep learning;
  • fluency in oral and written English is required as well as good presentation skills;
  • strong analytical as well as programming skills (C/C++, Java, Python, Shell scripting, etc.);
  • the candidate should be able to work in a research team.

Further 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.

Appointment

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. based on fulltime (38 hours a week), exclusive 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.

Job application

If you are interested and would like to apply for this job, please upload the following information 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. #LI-DNP     

No agencies please

Apply now