Phd Student In Neuromorphic Analog Calculator For Np-Hard Problem Solving With A Fpaa Platform (M/F)

Detalhes da Vaga

Organisation/Company: CNRS

Department: GEORGIATECH-CNRS

Research Field: Engineering Physics Technology

Researcher Profile: First Stage Researcher (R1)

Country: France

Application Deadline: 3 Dec 2024 - 00:00 (UTC)

Type of Contract: Temporary

Job Status: Full-time

Hours Per Week: 35

Offer Starting Date: 15 Jan 2025

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 PhD student will work in the "Photonic and Terahertz Imaging" team of IRL 2958 Georgia Tech-CNRS, located at Georgia Tech Europe in Metz. This team specializes in nonlinear dynamics, terahertz imaging, and analog computing. A key collaboration of the project will be with Prof. Jennifer Hasler of Georgia Tech Atlanta, a pioneer in the field of reconfigurable analog platforms (FPAA) and low-energy neuromorphic systems. The PhD student will benefit from direct access to her unique expertise, particularly for the implementation of the analog calculator on the FPAA platform. The PhD student will also interact regularly with internationally renowned researchers such as Prof. David Citrin and Dr. Alexandre Locquet. The project will offer a stimulating interdisciplinary research environment, with regular exchanges with experts in electronics, applied physics, and artificial intelligence.

This thesis project focuses on the development of an innovative neuromorphic analog computer, capable of solving NP-hard combinatorial optimization problems, such as the travelling salesman problem or the "max-cut" problem. Using a platform of reconfigurable analog circuits of the FPAA (Field-Programmable Analog Array) type, this project proposes to overcome the limitations of conventional digital systems by exploiting non-linear dynamics inspired by the human brain. This analog computing approach offers significant advantages in terms of energy efficiency and convergence speed, to tackle complex problems encountered in various scientific fields. The PhD student will work as part of an interdisciplinary team with experts from Georgia Tech-CNRS, Georgia Tech Atlanta, and CentraleSupélec, while developing cutting-edge expertise in nonlinear dynamics and neuromorphic computing.

Minimum Requirements

Master's degree in engineering or science.

Solid background in electronics, microelectronics, or analog systems.

Experience with analog or reconfigurable computing platforms (FPGA/FPAA).

Knowledge of non-linear dynamics or complex systems desirable.

Skills in combinatorial optimization and NP-hard problem solving desirable.

Interest in artificial intelligence and neuromorphic computing.

Ability to work independently in an interdisciplinary research environment.

Very good command of English.

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Salário Nominal: A acordar

Fonte: Allthetopbananas_Ppc

Função de trabalho:

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