Job offer

European Commission; France; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

A leading European research institution seeks a PhD student to join a renowned team focused on innovative research in neuromorphic computing. The successful candidate will engage in high-level supervision in a collaborative environment and work on advanced analog computing projects. This opportunity is ideal for individuals passionate about combining physics with computing to solve complex optimization problems.

Qualifications

• Strong command of analog circuits and microelectronics required.
• Interest in nonlinear dynamics and neuromorphic systems expected.
• Prior experience with combinatorial optimization advantageous.

Responsabilités

• Design a neuromorphic analog computer for combinatorial optimization.
• Collaborate within a dynamic international research environment.
• Engage in frequent interaction with leading scientists.

Connaissances

Autonomy

Analog circuits

Microelectronics

Reconfigurable computing

Unconventional computing

Formation

Master's degree or equivalent in electronics, applied physics, or related field

Description du poste

Organisation/Company CNRS Department GEORGIATECH-CNRS Research Field Engineering Physics Technology Researcher Profile First Stage Researcher (R1) Country France Application Deadline 8 Aug 2025 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Sep 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 join the Terahertz NDE and Nonlinear Dynamics team of the Georgia Tech-CNRS International Research Lab 2958, based at Georgia Tech Europe in Metz. This group is renowned for its expertise in nonlinear dynamics, terahertz imaging, and physics-based computation. The project is part of the ANR-funded AATLAS programme and involves close collaboration with Professor Jennifer Hasler (Georgia Tech Atlanta), a world leader in FPAA-based architectures. The student will benefit from high-level supervision and a dynamic research environment, with frequent interaction with leading scientists such as Prof. David Citrin and Dr. Alexandre Locquet.

This PhD project focuses on designing a neuromorphic analog computer capable of efficiently solving NP-hard combinatorial optimization problems, such as Max-Cut or 3-SAT. It leverages an innovative reconfigurable analog circuit platform (FPAA – Field-Programmable Analog Array), combining the energy efficiency and fast convergence of analog computing with the flexibility of digital processing. Inspired by Hopfield/Ising networks and non-linear dynamics, the research aims to overcome limitations inherent to traditional digital architectures.

Applicants should hold a Master's degree or equivalent in electronics, applied physics, or a related field. A strong command of analog circuits, microelectronics, or reconfigurable computing platforms (FPAA, FPGA) is required. A strong interest in unconventional computing, nonlinear dynamics, and neuromorphic systems is expected. Prior experience with combinatorial optimization or complex systems would be an advantage. The PhD candidate must demonstrate autonomy and be ready to contribute to a highly collaborative, interdisciplinary, and international research environment. Excellent proficiency in scientific English is essential.