PHD Machine learning-based design and test of cryogenic circuits for quantum computers (M/F)

Job Description

Thesis Subject

The design of cryogenic circuits has gained much importance in recent years, in particular for applications such as quantum computers, space exploration, and ultra-low-temperature sensing applications. Interface electronics with ultra-low levels of power consumption at temperatures as low as 4K are required. The design of these circuits is complicated due to the lack of standard design kits for their simulation at these temperatures. In addition, the traditional design methodologies that rely on empiric transistor models often require iterative simulations, making the process time-consuming and computationally expensive.
This research project aims to facilitate the design and test of cryogenic circuits using
machine learning (ML) techniques, focusing on 28 nm FD-SOI technology for the development of control and readout interfaces for silicon quantum bits. This thesis will consider the modeling, design and test of cryogenic devices and circuits, exploiting ML techniques for tasks such as: (1) the extraction of transistor models for AC, DC and noise analysis, with the models adapted for operation down to cryogenic temperatures; (2) the study of the correlations of circuit behavior with temperature that can be used for screening tests of cryogenic devices at room temperature; (3) the prediction and tuning of circuit behavior at cryogenic temperature as a function of room temperature measurements using data-driven models; (4) the analog synthesis and optimization of cryogenic circuits using reinforcement learning. In addition, generative AI techniques may be explored to propose novel circuit architectures suited for cryogenic conditions, exploiting the data-driven models extracted. The techniques developed will be demonstrated experimentally in silicon devices.

Desired skills
The candidate should hold an engineering degree in RF microelectronics and have experience using electronic computer-aided design (E-CAD) tools such as Cadence Virtuoso and Keysight ADS. Strong programming skills are required. Experience with AI tools and techniques would be considered an asset.

Your Work Environment

TIMA Laboratory is a public research laboratory jointly operated by the French National Centre for Scientific Research (CNRS), Grenoble INP-UGA, and Université Grenoble Alpes (UGA). It is located in Grenoble, France, on the Grenoble INP–UGA Viallet campus (46 Avenue Félix Viallet).
TIMA is a multicultural research environment comprising approximately 150 members from around the world, including permanent researchers, faculty members, PhD candidates, postdoctoral researchers, research engineers on fixed-term contracts, scientific collaborators, visiting researchers, and interns.
The laboratory's research activities cover the specification, design, verification, testing, electronic design automation (EDA) tools, and design methodologies for integrated systems. A significant portion of the research is carried out within the framework of collaborative projects involving industrial and academic partners, funded through regional, national, and European research programs. As a result, the laboratory maintains strong ties with both industry and academia, requiring a high level of professional engagement in both organizational and interpersonal activities.

The PhD will be carried between TIMA Laboratory and CEA-LETI in Grenoble, France, under the Q-loop project (Large Scale Quantum) of the Institut de Recheche Technologique Nanoelec, funded by the French National Research Council (CNRS).

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

The research professions