Ph.D. Student (M/F): Ferroelectric Memories for Capacitive Neuromorphic Computing & Frugal AI

Job Description

Thesis Subject

RESEARCH OPPORTUNITY: Von Neumann's electronic architecture is now reaching its energy limits, hindering the deployment of high-performance embedded AI. To overcome this bottleneck, neuromorphic electronics based on spiking neural networks (SNNs) and the compute-in-memory (CIM) paradigm is emerging as the most promising path. While the research community has so far favored resistive Compute-in-Memory using memristors, this approach faces physical barriers when scaling up: high static currents, Joule losses, leakage, and voltage drops (IR drop). This thesis project proposes a paradigm shift by turning to capacitive Compute-in-Memory via voltage summation. Thanks to the emergence of ferroelectric capacitive memories (memcapacitors), this approach offers an ultra-low-energy alternative, free from the imperfections of the resistive model and well-suited for NIS. We are seeking a Ph.D. student passionate about materials science, microelectronics, and artificial intelligence to develop high-performance memcapacitors and utilize them as artificial synapses for capacitive neuromorphic computing, enabling ultra-low-energy AI
SCIENTIFIC CHALLENGES: As part of a team of experts, you will lead the following areas of research:
• Microfabrication and materials innovations: Development of cleanroom processes to fabricate capacitive memories in crosspoint and crossbar architectures. You will explore (Gd, Zr, La)-doped HfO₂ as a reference ferroelectric layer and optimize performance (memory window, multilevel writing, endurance) through the fine-tuning of thin films (interlayers, superlattices) and electrodes (Ru, Mo).
• State-of-the-art characterization: Memcapacitors will be studied using advanced physicochemical (XRD, XRR, XPS, TEM) and electrical characterization techniques. You will develop semi-automated characterization protocols (I-V, C-V, pulsed) on samples and 300-mm wafers. You will analyze the variability in write and read capacitance levels, a critical factor for the performance of hardware neural networks.
• Contribution to neuromorphic demonstrators: You will actively participate in the development of capacitive neuromorphic circuits and in in-memory computing demonstrations (charge or voltage summation). This work will be part of a collaborative effort, involving constant interaction with other researchers on the team (Ph.D. students, postdocs, interns) working on system integration and modeling.

You hold a master's degree or engineering degree in Microelectronics, Materials Science, or Nanotechnology, and have a proven track record of academic excellence and hands-on experience in cleanroom environments and/or electrical characterization. Scientific rigor, independence, curiosity, and fluency in technical English are required. You have a particular interest in emerging memory technologies and bio-inspired technologies for AI.

Your Work Environment

AN EXCEPTIONAL ENVIRONMENT IN EUROPE: The thesis will be conducted at the Microelectronics Technology Laboratory (LTM), a core member of LabEx Microelectronics, at the heart of Europe's largest R&D hub for nanotechnology. The LTM is a joint CNRS/Université Grenoble Alpes research unit comprising six teams—four of which are research teams—and employs approximately 90 people. The laboratory is located at the CEA-LETI site in Grenoble. • Technology platforms: You will have direct access to the state-of-the-art cleanrooms of the Upstream Technology Platform (PTA) and CIME Nanotech, which operate manufacturing lines up to 200 mm—a rarity in the academic world. • Network & Collaborations: Your work will be supported by strategic collaborations with LabEx member laboratories (CEA-LETI, CROMA, TIMA, LMGP) for the development of processes, advanced metrology, and neuromorphic circuits. • Excellence in Training: You will develop a unique hybrid profile (materials, fabrication, neuromorphic electronics) within a world-renowned interdisciplinary ecosystem that fosters innovation and scientific excellence. There is an opportunity to complete a 6-month internship at another academic or industrial research laboratory specializing in ferroelectric devices and neuromorphic electronics.

Constraints and risks

none

Compensation and benefits

Compensation

2300 € gross monthly

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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