08/03/2021
The Human Resources Strategy for Researchers

PhD student position: ROBUSTNESS AND RELIABILITY IN PHOTONIC NEURAL NETWORKS

This job offer has expired


  • ORGANISATION/COMPANY
    Ecole Centrale de Lyon / Lyon Institute of Nanotechnologies
  • RESEARCH FIELD
    EngineeringComputer engineering
    EngineeringElectronic engineering
    PhysicsOptics
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    15/05/2021 00:00 - Europe/Brussels
  • LOCATION
    France › Ecully
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    35
  • OFFER STARTING DATE
    01/10/2021

OFFER DESCRIPTION

Today, the exponential growth in the amount of data (e.g., generated by IoT devices) calls for innovative computing approaches that can circumvent the electrical I/O bottleneck and increase computing performance of next-generation systems. Many efforts are currently ongoing to explore and demonstrate novel unconventional (non-Von-Neumann) computing architectures. Specifically, brain-inspired (neuromorphic) hardware architectures can deliver several orders of magnitude superior performance in terms of energy efficiency, computation density, speed and latency compared to classical CPU and GPU-based computing solutions. Several applications ranging from 5G technology and IoT processing to autonomous driving and robotics would greatly benefit from such solutions.

The focus of this work will be to develop neuromorphic architectures leveraging emerging technologies suitable for the implementation of these novel computing paradigms. Among the myriad of technologies under investigation, integrated photonics is regarded as one of the best candidates because of its large potential in terms of multiplexing (parallelization), high-speed operation and speed-of-light propagation as well as low power consumption and large number of physical degrees to manipulate/encode the information (amplitude, polarization, phase, etc.). Besides, integrated photonics benefits from CMOS-compatible fabrication for volume scaling and ease of market take-up.

In the framework of a research project funded by the French National Research Agency (ANR) and by the University of Lyon, the Heterogeneous Systems Design group at INL aims to explore the limitations in terms of robustness and reliability of photonic neural networks. In this context we are currently looking for a (m/f) PhD student for a 3-year contract.

This thesis aims to explore the robustness and reliability of photonic neural networks (neuromorphic architectures) and to propose solutions at a device/system level to enhance their performance for real scenarios deployment.

This will involve (i) selecting key photonic neuromorphic architectures, (ii) carrying out their behavioral and system-level modeling, (iii) assess their performance in terms of robustness and reliability by exploiting techniques well-known in the reliability community, and (iv) propose novel device/system designs and strategies to build more robust and reliable architectures.

The work will involve behavioral and system-level modeling of photonic devices and neuromorphic architectures, robustness and reliability analysis of the selected architectures, and the proposal of novel design/system-level solutions.

About INL

INL is a 250-strong research institute based in Lyon, France, carrying out fundamental and applied research in electronics, semiconductor materials, photonics and biotechnologies. The Heterogeneous Systems Design group is a leader in the area of advanced nanoelectronic design, with research projects and collaborations at both national and European level. Recent highlights include the development of high-performance design strategies for complex 3D integrated circuits, ferroelectric logic in memory, VNWFET-based logic and silicon photonic networks on chip.

More Information

Benefits

Total gross salary of 2,845 €/month (including social benefits; e.g. pension, health and unemployment insurance). This corresponds to a net salary of approximately 1,600 €/month.

Eligibility criteria

The successful candidate must be authorized for security clearance to work at Lyon Institute of Nanotechnology. Pre-employment screening and background checks will be carried out in this regard.

Selection process

CV and statement of purpose (in English or French) must be sent by email to Dr. Fabio Pavanello and Prof. Alberto Bosio:

The selection process will be carried out in two steps:

  • initial screening based on application documents (full CV, support letters)
  • if the screening stage is successful, the candidate will be invited to interview (face-to-face or remote)

Required Research Experiences

  • RESEARCH FIELD
    Physics
  • YEARS OF RESEARCH EXPERIENCE
    1 - 4
  • RESEARCH FIELD
    Engineering
  • YEARS OF RESEARCH EXPERIENCE
    1 - 4
  • RESEARCH FIELD
    Computer science
  • YEARS OF RESEARCH EXPERIENCE
    1 - 4

Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Engineering: Master Degree or equivalent
    Physics: Master Degree or equivalent
    Computer science: Master Degree or equivalent
  • REQUIRED LANGUAGES
    ENGLISH: Excellent

Skills/Qualifications

You have or are about to obtain an MSc in Electronic or Physical Engineering / Computer Engineer / Computer Science with strong experience in at least one of the following areas: analog / digital / photonic integrated circuit design, multi-disciplinary or system-level modelling. Good programming skills (python, C++) are required. Previous experience in Neural Networks is a plus (e.g., knowledge of major NN frameworks such as Pytorch and Tensorflow). Excellent written and verbal communication skills in English. Fluency in French is also a plus but is not mandatory.

Work location(s)
1 position(s) available at
Ecole Centrale de Lyon / Lyon Institute of Nanotechnologies
France
France
Ecully
69130
36, av Guy de Collongue

EURAXESS offer ID: 612791

Disclaimer:

The responsibility for the jobs published on this website, including the job description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.

 

Please contact support@euraxess.org if you wish to download all jobs in XML.