Inria, France invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at Inria, France.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Signal processing-based on the squared eigenfunctions of the Schrodinger operator. Application to EEG signals
Biomedical signals are usually characterized by the presence of peaks that provide direct or indirect information on the physiological and metabolic state. Usually, these pulse-shaped signals require preprocessing such as denoising and artifact removals. Further analysis and processing might be required in some specific situations to allow for the extraction of pertinent information from these signals. Despite the fact that the literature abounds with signal processing methods, there are still challenges that need to be overcome and further improvements can be achieved for processing pulse-shaped signals. In this context, a quantum-based signal processing method has been proposed in 1. This method called the semi‐classical signal analysis (SCSA) method decomposes the signal into a set of functions given by the squared eigenfunctions of the Schrödinger operator associated with its negative eigenvalues 1. Thus, and unlike traditional signal decomposition tools, the SCSA expresses the signal through a set of functions that are signal dependent, that is, these functions are not fixed and known in advance but are computed by solving the spectral problem of the Schrödinger operator whose potential is the signal to be analyzed. Accordingly, these eigenfunctions capture more details about the signal and its morphological variations 2. The SCSA has been successfully applied in many applications for signal representation, denoising, post‐processing, and feature extraction. For example, it has been used for arterial blood pressure waveform analysis in 3,4 and for magnetic resonance spectroscopy (MRS) denoising 5, for MRS water suppression 6, and for MRS lipid suppression 7. It has been also used for feature extraction in epileptic seizure detection 8 and for the characterization of PPG signals and blood pressure signals for non-invasive estimation of central pressure and arterial stiffness respectively 9. Recent work on the characterization of EEG signals for epileptic seizure detection and seizure onset zone location has shown promising results 10, 11.
Deadline : 2026-09-30
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Modeling and Simulation of Exascale Storage Systems
The Inria Rennes – Bretagne Atlantique Centre is one of Inria’s eight centres and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.
Deadline : 2024-12-31
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD position F/M Building physics-based multilevel surrogate models from neural networks. Application to electromagnetic wave propagation
Numerical simulations of electromagnetic wave propagation problems primarily rely on a space discretization of the system of Maxwell’s equations using methods such as finite differences or finite elements. For complex and realistic three-dimensional situations, such a process can be computationally prohibitive, especially when the end goal consists in many-query analyses (e.g., optimization design and uncertainty quantification). Therefore, developing cost-effective surrogate models is of great practical significance.
There exist different possible ways of building surrogate models for a given system of partial differential equations (PDEs) in a non-intrusive way (i.e., with minimal modifications to an existing discretization-based simulation methodology). In recent years, approaches based on neural networks (NNs) and Deep Learning (DL) have shown much promise, thanks to their capability of handling nonlinear or/and high dimensional problems. Model-based neural networks, as opposed to purely data-driven neural networks, are currently the subject of intense research for devising high-performance surrogate models of parametric PDEs.
Deadline : 2024-11-30
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD student F/M Bandit theory for personalized patient monitoring.
The Inria University of Lille center, created in 2008, employs 360 people including 305 scientists spread across 15 research teams. Recognized for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria center at the University of Lille maintains a close relationship with large companies and SMEs. By promoting synergies between researchers and industrialists, Inria participates in the transfer of skills and expertise in the field of digital technologies and provides access to the best of European and international research for the benefit of innovation and businesses, particularly in the region.
Deadline : 2024-08-01
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Fast solvers for studying light absorption by nanostructured imagers
The exploitation of nanostructuring in order to improve the performance of CMOS imagers based on microlens grids is a very promising avenue. In this perspective, numerical modeling is a key component to accurately characterize and optimize the absorption properties of these complex imaging structures which are intrinsically multiscale (from the micrometer scale of the lenses to the nanometric characteristics of the nanostructured material layers). The present PhD project is proposed in the context of a collaboration between the Atlantis project-team of Inria research center at Université Côte d’Azur and STMicrolectronics (CMOS Imagers division of the Technology for Optical Sensors department) in Crolles. A Cifre funding will support this project.
Deadline : 2024-06-30
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(06) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Designing highly efficient ultrafast dynamical metasurface for LIDAR applications
The present postdoctoral project is part of a collaborative project between the Atlantis project-team from the Inria Research Center at Université Côte d’Azur, (2) CRHEA in Sophia Antipolis, France, and (3) LAAS in Toulouse France.
Atlantis is a joint project-team between Inria and the Jean-Alexandre Dieudonné Mathematics Laboratory at Université Côte d’Azur. The team gathers applied mathematicians and computational scientists who are collaboratively undertaking research activities aiming at the design, analysis, development and application of innovative numerical methods for systems of partial differential equations (PDEs) modelling nanoscale light-matter interaction problems. In this context, the team is developing the DIOGENeS [https://diogenes.inria.fr/] software suite, which implements several Discontinuous Galerkin (DG) type methods tailored to the systems of time- and frequency-domain Maxwell equations possibly coupled to differential equations modeling the behaviour of propagation media at optical frequencies. DIOGENeS is a unique numerical framework leveraging the capabilities of DG techniques for the simulation of multiscale problems relevant to nanophotonics and nanoplasmonics.
Deadline : 2024-05-31
(07) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD Position F/M Interacting with Avatars in Virtual and Augmented Reality
This PhD position is framed in the context of the ANR project ASTRAL (Augmented Self: TowaRds effective Avatars in augmented reality). The general context of this project is the design and study of avatars in augmented reality. Avatars, i.e. digital representations of users in a Virtual Environment (VE) [1], are more and more present in our lives due to the recent democratization of Virtual Reality (VR) headsets and supported by the colossal investments of major economic actors such as Meta or Microsoft. Avatars today are the most broadly used means for representing users in an immersive VE and can be found in a wide range of applications in areas such as entertainment, tele-communication, medicine, education, etc. Such avatars have been shown to improve users’ presence [2] and performance [3] in immersive VEs, and even alter their perceptions [4]. Our general objective is therefore to enable and evaluate AR avatarization (i.e. providing users with their own AR avatar). Reaching this objective will help us pave the way to new innovative AR avatars by proposing new rendering and interaction methods along with perceptual understanding of their use. Considering this general objective, we will focus our efforts on three scientific objectives. This PhD will focus on the interaction dimension, and in particular on the “Interacting through AR avatars”. We envision the AR avatar as an interaction tool that will augment the user’s interaction capabilities, enabling the interaction with real and augmented content.
Deadline : 2024-03-31
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Aerial Robots with the sense of touch
The Inria Center at Rennes University is one of Inria’s eight centers and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative SMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.
Deadline : 2024-03-21
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(09) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Reliable Deep Neural Network Hardware Accelerators
Deep Neural Networks (DNNs) [1] are currently one of the most intensively and widely used predictive models in the field of machine learning. DNNs have proven to give very good results for many complex tasks and applications, such as object recognition in images/videos, natural language processing, satellite image recognition, robotics, aerospace, smart healthcare, and autonomous driving. Nowadays, there is intense activity in designing custom Artificial Intelligence (AI) hardware accelerators to support the energy-hungry data movement, speed of computation, and memory resources that DNNs require to realize their full potential [2]. Furthermore, there is an incentive to migrate AI from the cloud into the edge devices, i.e., Internet-of-Things (IoTs) devices, in order to address data confidentiality issues and bandwidth limitations, given the ever-increasing internet-connected IoTs, and also to alleviate the communication latency, especially for real-time safety-critical decisions, e.g., in autonomous driving.
Deadline : 2024-02-28
(10) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M PhD student on federate learning and multi-party computation techniques for prostate cancer
While AI techniques are becoming ever more powerful, there is a growing concern about potential risks and abuses. As a result, there has been an increasing interest in research directions such as privacy-preserving machine learning, explainable machine learning, fairness and data protection legislation.
Privacy-preserving machine learning aims at learning (and publishing or applying) a model from data while the data is not revealed. Notions such as (local) differential privacy and its generalizations allow to bound the amount of information revealed.
The goal of the multi-disciplinary FLUTE project is to advance and scale up data-driven healthcare by developing novel methods for privacy-preserving cross-border utilization of data hubs. Advanced research will be performed to push the performance envelope of secure multi-party computation in Federated Learning, including the associated AI models and secure execution environments.
Deadline : 2024-01-31
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(11) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Guaranteed Fairness in Machine Learning
The Inria University of Lille centre, created in 2008, employs 360 people including 305 scientists in 15 research teams. Recognised for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria University of Lille centre pursues a close relationship with large companies and SMEs. By promoting synergies between researchers and industrialists, Inria participates in the transfer of skills and expertise in digital technologies and provides access to the best European and international research for the benefit of innovation and companies, particularly in the region.
Deadline : 2024-01-31
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(12) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Self-supervised learning for implicit shape reconstruction
The Inria Rennes – Bretagne Atlantique Center is one of Inria’s eight centers and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative SMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.
Deadline : 2024-01-31
(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Spatial statistics and machine learning for molecular dynamics analysis in 2D/3D microscopy
The thesis will take place in the SAIRPICO project-team, which is specialized in the development of innovative methods for image restoration/reconstruction, motion analysis and computation of molecular trajectories in live cell imaging, and biophysical parameter estimation. The thesis we propose is at the frontier of applied mathematics, image processing/analysis, machine learning, and computer science. The goal is to develop statistical and machine learning methods and algorithms for analyzing intracellular motion and molecular dynamics observed in vector-valued microscopy images.
Deadline : 2024-01-31
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Topology Design for Decentralized Federated Learning
The Inria centre at Université Côte d’Azur includes 37 research teams and 8 support services. The centre’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d’Azur, CNRS, INRAE, INSERM …), but also with the regiona economic players.
With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d’Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.
Deadline : 2024-01-28
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Distributed Training of Heterogeneous Architectures
Inria is a national research institute dedicated to digital sciences that promotes scientific excellence and transfer. Inria employs 2,400 collaborators organized in research project teams, usually in collaboration with its academic partners.
This agility allows its scientists, from the best universities in the world, to meet the challenges of computer science and mathematics , either through multidisciplinarity or with industrial partners.
A precursor to the creation of Deep Tech companies, Inria has also supported the creation of more than 150 start-ups from its research teams. Inria effectively faces the challenges of the digital transformation of science, society and the economy.
Deadline :2024-01-28
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Dynamically Configurable Deep Neural Network Hardware Accelerators
The Inria Center of Rennes University is one of Inria’s eight centers and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative SMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.
Deadline : 2024-01-14
(17) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Verified Offloading Orchestration of Network Functions at the Edge
The offered position is proposed by the RESIST team of the Inria Nancy Grand Est research lab, the French national public institute dedicated to research in digital Science and technology. The team is one of the European research group in network management and is particularly focused on empowering scalability and security of networked systems through a strong coupling between monitoring, analytics and network orchestration.
Deadline : 2023-12-31
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Monitoring Plane for mobile cellular networks
The Inria Université Côte d’Azur center counts 37 research teams as well as 8 support services. The center’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The majority of the center’s research teams are located in Sophia Antipolis and five of them are based in an Inria antenna in Montpellier. The Inria branch in Montpellier is growing in size, in accordance with the strategy described in the institution’s Contract of Objectives and Performance (COP).
Deadline : 2023-12-31
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Experimental evaluation of sliced cellular networks
The overall objective of the DIANA project-team is to design, implement and evaluate advanced networking architectures. To do so, the team works to provide service transparency and programmable network deployments in the context of both wired and next generation wireless cellular networks. The team’s methodology includes advanced measurement techniques, design and implementation of architectural solutions, and their validation in adequate experimental facilities. The DIANA team designed, deployed and operates R2lab, a wireless testbed designed with reproducibility as its central characteristics. The team collaborates with Eurecom to deploy and operate an open programmable platform to test post-5G services. Recently, the team enriched R2lab with 5G professional radio units and compute resources managed by Kubernetes clusters to provide an experimental cloud-native environment to test with open source (OAI, SrsLTE) software and some commercially licensed software (e.g. Amarisoft) for 5G/6G networks supporting for example scenarios with disaggregated 5G networks elements. Other recent contributions of the team include: Enhanced Transport-Layer Mechanisms for Multi-Access Edge Computing-Assisted Cellular Networks, Bencharmking Mobile Networks from the Viewpoint of Video Streaming QoE, Introducing Fidelity in Network Emulation, and Enhanced Ray Tracing Techniques for Accurate Estimation of Signal Power.
Deadline : 2023-12-31
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(20) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Socially-Aware Embodied Conversational Agents: Achieving Task and Social Goals in Human-Computer Conversation with students
The objective of this project is to build embodied conversational agents (also known as ECAs, or virtual humans, or chatbots, or multimodal dialogue systems) that have the ability to engage their users in both social and task talk, where the social talk serves to improve task performance. In order to achieve this objective, we model human-human conversation, and integrate the models into ECAs, and then evaluate their performance. This position is a 3-4 year doctoral contract.
Deadline : 2023-12-31
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Towards more solid basis for symmetric cryptography
During this PhD we will work on generalizing and improving the existing cryptanalysis families on symmetric cryptography.
Deadline : 2023-12-31
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M The role of rapport in human-conversational agent interaction: Modeling conversation to improve task performance in human-agent interaction
The objective of this project is to build embodied conversational agents (also known as ECAs, or virtual humans, or chatbots, or multimodal dialogue systems) that have the ability to engage their users in both social and task talk, where the social talk serves to improve task performance. In order to achieve this objective, we model human-human conversation, and integrate the models into ECAs, and then evaluate their performance.
This project is located at the prestigious computer science institute INRIA in downtown Paris. It takes place in the context of the PRAIRIE Institute for Interdisciplinary Research on AI – one of the four 3IA institutes launched by the French government in 2019.
Deadline :2023-12-31
(23) PhD Degree – Fully Funded
PhD position summary/title: PhD student F/M On the design of an improved Boussinesq model for real applications: balance between precision and performance
The thesis will take place within the framework of a research agreement between the BRGM and the Nouvelle-
Aquitaine region. This is a thesis funded by the BRGM which will benefit from INRIA/BRGM supervision.
Deadline : 2023-12-31
(24) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M A proof theoretic approach of polymorphic instantiation
This position is in the context of a collaboration between Gabriel Scherer (INRIA Saclay) and Paolo Pistone (ENS Lyon). Regular visits between both places are planned, and will of course be funded, in addition to usual scientific travel.
Deadline : 2023-12-31
(25) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Contention-Aware Scheduling of Storage Resources on Exascale Systems
The Inria Rennes – Bretagne Atlantique Centre is one of Inria’s eight centres and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.
Deadline : 2023-12-31
(26) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Adoption dynamics in social networks for green mobility
This work will be carried out in the DANCE team (Dynamics and Control of Networks), a research team of GIPSA-Lab research center in Grenoble, France. The team’s research concerns modeling, estimation and control of network systems, with a broad spectrum of theoretical and applied topics including traffic networks, intelligent vehicles, social dynamics, and analysis of large-scale complex networks.
The thesis is part of the FORBAC project funded by the French government within the PEPR “DATA TECHNOLOGY for MOBILITY IN THE TERRITORIES”. The activities of the PhD thesis will be hosted at the Grenoble INRIA Center.
Deadline : 2023-12-31
(27) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Massively Multi-User Wireless Communications
Wireless connected devices such as smartphones, computers and TVs, autonomous cars, watches, sensors, lightbulbs and numerous sensors proliferate as our lifestyle becomes increasingly intertwined with digital services. From the point of view of communications networks, these devices give rise to a new class of data traffic, more sporadic, and for some applications requiring more stringent reliability guarantees than what classical mobile broadband can offer. In particular, the mechanisms and protocols classically used to mitigate transmission collision between randomly activated transmitters are not efficient in the new regime of many users and small payloads. A significant breakthrough was made with the introduction of the unsourced random access paradigm [P17]; one of the proposed approaches is based on the use of multi-linear spreading as a modulation, which allows convenient user separation at the receiver using tensor algebraic considerations [DLG21]. The object of the proposed study is to develop modulations and waveforms for massive multi-user wireless communications that can be applied to a wide class of propagation channels, including multipath and time-varying channels, and support asynchronous or quasi-synchronous operation.
Deadline : 2023-12-31
(28) PhD Degree – Fully Funded
PhD position summary/title: PhD thesis Seamless Shared Urban Mobility, Integrated scheduling
Deadline :2023-12-29
(29) PhD Degree – Fully Funded
PhD position summary/title: PhD thesis (H/F) Seamless Shared Urban Mobility, Incentive design
Deadline :2023-12-29
(30) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M 3-year PhD position in Automatic Argumentation Mining in French Legal Decisions
We invite applications for a 3-year PhD position co-funded by Inria, the French national research institute in Computer Science and Applied Mathematics, and LexisNexis France, leader of legal information in France and subsidiary of the RELX Group.
The position is affiliated with the MAGNET, a research group at Inria, Lille, which has expertise in Machine Learning and Natural
Language Processing, in particular Discourse Processing. The PhD student will also work in close collaboration with the R&D team at
LexisNexis France, who will provide their expertise in the legal domain and the data they have collected.
Deadline : 2023-12-29
(31) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Machine learning and optimization methods for 3D vector-valued microscopy image reconstruction
Unlike conventional fluorescence microscopy, the new generation of polarized light-based microscopy instruments allow one to probe the orientation of fluorescently tagged biomolecules in cells. As the generated data are now 3D+time vector-valued signals encompassing density and orientation of molecules, serious challenges in signal and image processing need to be solved before being able to fully exploit the potential of polarized microscopy in biological studies. The aim of of this thesis is then to develop the next generation of information processing techniques for microscopy and bioimaging. This will be achieved through the development of a new methodological framework based on the principled approach of supervised and unsupervised and sparse image representations for vector-valued image data. The new unifying framework will be able to manage heterogeneous data and models in optics and biophysics. Our hope is to build a framework, connected to several theories in statistics, such as Bayesian methods and nonparametric estimation, flexible enough to be combined with machine learning techniques, and able to address tasks going from image reconstruction to spatial high-resolution estimation of molecular motion. Our case-studies in cell biology will be related to the analysis of intracellular trafficking and molecule transport pathways, as they represent a major contributory factor to a number of diseases such as cancer, and viral infection. The advances iwill result in a new generation of algorithms for 3D polarized microscopy instruments, which will be widely used in the future for applications in precision medicine, with a high potential impact for other vector-valued image modalities and other inverse problems in bioimaging.
Deadline :2023-12-27
(32) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Reliability and Security of Large Foundation Models
Large Foundation Models (LFMs) are cutting-edge technology for natural language processing, object detection and segmentation, and audio and multimodal processing, outperforming any available machine learning technique. LFMs, such as OpenAI GPT-4, Google ViT, and Meta LLaMA, have gained public attention with their unprecedented accuracy. Given the superior performance of LFMs, they are being deployed in safety-critical and mission-critical applications, including space exploration and self-driving cars. Improving LFMs’ security and reliability is crucial to enable dependable real-time safety-critical systems.
Deadline : 2023-12-25
(33) PhD Degree – Fully Funded
PhD position summary/title: PhD Position F/M Exploring the variability induced by different configurations in the neuroimaging analytical space
The goal of brain imaging is to provide in-vivo measures of the human brain to better understand how the brain is structured, connected and functions. Neuroimaging studies are characterised by a very large analysis space and, to build their analyses, practitioners must choose between different software, software versions, algorithms, parameters, etc. For many years, those choices have been considered as “implementation details” but evidence is growing that the exact choices of analysis strategy can lead to different and sometimes contradictory results (Botvinik-Nezer et al., 2020).
Deadline : 2023-12-23
About The National Institute for Research in Computer Science and Automation (Inria), France –Official Website
The National Institute for Research in Computer Science and Automation (Inria) is a French national research institution focusing on computer science and applied mathematics. It was created under the name Institut de recherche en informatique et en automatique (IRIA) in 1967 at Rocquencourt near Paris, part of Plan Calcul. Its first site was the historical premises of SHAPE (central command of NATO military forces), which is still used as Inria’s main headquarters. In 1980, IRIA became INRIA. Since 2011, it has been styled Inria.
Inria is a Public Scientific and Technical Research Establishment (EPST) under the double supervision of the French Ministry of National Education, Advanced Instruction and Research and the Ministry of Economy, Finance and Industry.
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