Neuro-inspired computing (e.g. reservoir computing) in coupled Double-Drum nanoelectromechanical resonator networks

CNRS

France

Vor Ort

EUR 38.000 - 48.000

Vollzeit

14 Tage+

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Zusammenfassung

CNRS IEMN invites applications for a postdoctoral researcher to develop reservoir computing in a coupled nanoelectromechanical system based on double-drum resonators. The project builds on NOEMIA and MORETOME work and aims to push unconventional hardware for AI.

The candidate should have a PhD in nanoelectromechanics, multi-physics modelling, optomechanics, or high frequency devices, strong programming skills in Python or MATLAB, and excellent written and spoken English.

Qualifikationen

  • PhD in nanoelectromechanics or multi-physics modelling, optomechanics, or high frequency devices.
  • Strong programming skills in Python or MATLAB.
  • Excellent written and verbal English; French is a plus.

Aufgaben

  • Develop reservoir computing functionality using a coupled NEMS network of double-drum resonators.
  • Perform numerical simulations and experimental validation of nonlinear dynamics.
  • Collaborate with CNRS IEMN researchers and external partners.
  • Document methods and results for publication and dissemination.

Kenntnisse

Programming (Python or MATLAB)
English communication
Teamwork & autonomy

Ausbildung

PhD in nanoelectromechanics or multi-physics modelling or optomechanics or high frequency devices

Tools

MATLAB
Python
Lock-in amplifier
Oscilloscope
FPGA

Jobbeschreibung

Institute of Electronics, Microelectronics and Nanotechnology

Organisation/Company CNRS IEMN Department Institute of Electronics, Microelectronics and Nanotechnology Research Field Engineering » Microengineering Physics » Applied physics Engineering » Electronic engineering Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 30 Nov 2026 - 16:06 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 37 Offer Starting Date 1 Dec 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The French team at IEMN has developed a unique nanoelectromechanical resonator (NEMS) consisting of a silicon nitride drum capacitively coupled to an aluminium drum resonator, referred to as a double-drum resonator[1]. The team has recently achieved in implementing reservoir-computing in the coupled drum resonators and successfully fabricated networks of coupled double-drum resonators [2], based on the European CHIST-ERA NOEMIA project and the French ANR-MORETOME project. To date, basic reservoir-computing functionality and the training of an artificial neural network have been demonstrated using a single device.The main mission of this postdoc project, financially supported by IMITECH project, is to develop reservoir computing function based on a coupled NEMS network, consisting of 2 or more double-drum resonators. This is beyond current state of art and relies on deep understand of more degrees of nonlinear complexity of the coupled resonator networks. The achievement of this project will bring a new unconventional scheme to next generation hardware for AI.

We are looking for a highly motivated candidate who has either engineering profile in domains of nonlinear dynamics, optomechanics/nanomechanics, or signal processing. You have or are about to obtain a PhD in at least one of the following areas: nanoelectromechancics, OR multi-physics modelling (numerical simulations, e.g. matlab or python, or analytical modeling), OR optomechanics, OR high frequency devices.You are eager to learn and expand your knowledge! Basic knowledge of analog and digital circuits. Experience with various techniques for high frequency characterization, e.g., lockin amplifier, oscilloscope, FPGA, and so on. Mandatory experience in programming (e.g. python or matlab). Excellent written and verbal communication skills in English. Fluency in French is also a plus, but not mandatory. You have abilityto contribute effectively in a team environment while also working autonomously when required

The Institute of Electronic, Microelectronic and Nanotechnology (UMR CNRS 8520 – https://www.iemn.fr/en/ ) is in Villeneuve D'Ascq, close to the city of Lille (France). We offer reservoir computing measurement setup, high frequency NEMS characterization platform, numerical simulators, and multiphysics environment. The recruited Postdoc will be trained and technically supported by CNRS permanent researchers in IEMN.The candidate is expected to work autonomously as well as in collaboration with a research team. For more details, please feel free to contact with the PI by email: xin.zhou@cnrs.fr or xin.zhou@iemn.fr

Requirements

Research Field Physics Education Level PhD or equivalent

Research Field Engineering Education Level PhD or equivalent

Skills/Qualifications

We are looking for a highly motivated candidate who has either engineering profile in domains of nonlinear dynamics, optomechanics/nanomechanics, or signal processing. You have or are about to obtain a PhD in at least one of the following areas: nanoelectromechancics, OR multi-physics modelling (numerical simulations, e.g. matlab or python, or analytical modeling), OR optomechanics, OR high frequency devices.You are eager to learn and expand your knowledge! Basic knowledge of analog and digital circuits. Experience with various techniques for high frequency characterization, e.g., lockin amplifier, oscilloscope, FPGA, and so on. Mandatory experience in programming (e.g. python or matlab). Excellent written and verbal communication skills in English. Fluency in French is also a plus, but not mandatory. You have abilityto contribute effectively in a team environment while also working autonomously when required.

Specific Requirements

Mandatory experience in programming (e.g. python or matlab)

Languages ENGLISH Level Good

Research Field Engineering » MicroengineeringPhysics » Applied physicsEngineering » Electronic engineering Years of Research Experience 1 - 4

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