Current theses

what if your curiosity deserved a few more years to get to the bottom of a question ?

At 3iL Ingénieurs, pursuing a Ph.D. simply means continuing your journey in an environment where curiosity, exploration, and the desire to understand are fully embraced.

Here, research isn’t limited to an isolated academic setting: it takes shape in concrete projects, in close collaboration with well-known laboratories and teams working on the major scientific and technological challenges of today and tomorrow.

what you truly develop through your ph.d

You learn to take a step back, deeply explore a question, and develop your own unique expertise—while staying connected to real-world uses and applications. It’s not a one-way trip to pure theory: it’s a constant back-and-forth between research and practical application.

At 3iL, this commitment is part of a supportive and structured mentoring program. Each doctoral student progresses within an ecosystem that values scientific rigor as much as openness, innovation, and collaboration.

Ronald Moussitou (2023-2026)

AI and Mathematics Education: How Does the Integration of AI Systems Affect Teachers’ Work?

When it comes to teaching mathematics, teachers face a variety of challenges, including engaging students who are prone to getting bored or distracted, motivating students with little interest, managing math anxiety, fostering genuine understanding among passive students, providing sufficient opportunities for practice, assessing progress in a context where answers are readily available, and managing students’ varying levels of preparation. However, given that teachers often have limited time to devote to students, addressing these challenges is a challenge in itself.

Extensive research on artificial intelligence (AI) in mathematics education (AIME) suggests that the use of AI systems could have a significant impact on teachers. Therefore, the central question is how to meaningfully integrate these AI systems to enable teachers to benefit from their effects and help them overcome these challenges. Could the successful integration of these AI systems make it possible to accurately identify the specific changes in the profession of teaching mathematics?

Maxime Balloufaud (2022-2025)

TERAPACE Project (Augmented Reality Telerehabilitation for Cerebral Palsy): An Augmented Reality Exergame for the Cognitive-Motor Rehabilitation of Children and Adolescents with Cerebral Palsy (CP) or Acquired Brain Injury (ACL)

Rehabilitation programs for children and adolescents with CP or ACL are not easily accessible, which hinders the development of their physical and cognitive abilities. The COVID-19 pandemic has highlighted the need for specific care interventions for these children and their families. As part of these children’s rehabilitation, it is necessary to offer cognitive-motor or spatial navigation rehabilitation programs that incorporate various sensory stimuli (visual, auditory). In this context, new technologies appear to be a relevant solution for providing playful and personalized rehabilitation, with the possibility of conducting remote self-rehabilitation. Virtual reality is commonly used in pediatric rehabilitation, whereas augmented reality is a very recent and promising technology. Before studying the effectiveness of a new augmented reality-based program, it is essential to evaluate the usability, user experience, acceptance, and potential benefits of this type of device in cognitive-motor rehabilitation for this population.

We have developed an exergame using an augmented reality headset that will ultimately offer a new form of rehabilitation; one that is both fun and interactive for children and adolescents with cerebral palsy (CP) or motor learning disorders.

This project is based on three operational objectives:

The first one is to design and develop an augmented reality device.
The second objective is to evaluate the device’s usability, user experience, acceptance, and motivation.
The third one is to study the feasibility of deploying the device in patients’ homes for use by patients and their families.

Gabriel Valenti (2022-2025)

Development of a Radar Signal Processing Platform for High-Resolution Detection

In this work, we focus on the surveillance and tracking of space objects in low Earth orbit. Monitoring space debris is now a priority for space agencies, given the serious threat these objects pose to satellites and space missions. Detecting targets and determining their parameters with high precision in a noisy environment (unwanted echoes, radar clutter, interference, etc.) remains challenging. The development of signal processing algorithms combined with artificial intelligence techniques offers a solution to these limitations. In this thesis, we propose to explore the contribution of machine learning and deep learning techniques to the challenges of radar signal processing and analysis for high-resolution detection: parameter estimation and target tracking. The major challenge in developing artificial intelligence techniques for radar is the availability of training data. The objectives of this thesis are therefore to:

Implement AI techniques to improve detection and resolution.
Develop a high-resolution multi-antenna radar simulator for space applications
Implement an experimental platform for radar signal processing
Create a training database using simulated and measured data

Michael Law San (2022-2025)

Hybrid and Distributed Perception and Mapping for Heterogeneous Multi-Robot Systems in Open Environments

The objective of this dissertation is to study and advance the state of the art in multimodal perception fusion for a cooperative, distributed, heterogeneous robot system. The goal of multimodal fusion is to obtain a unified representation based on the robots’ various sensors, while also leveraging their complementary nature. It is important to note that, as with any observation system, there will be inconsistencies—spatial, temporal, and those due to noise inherent to the sensors. With this unified representation, the heterogeneous robot system will be able to self-organize to accomplish missions. Various multimodal fusion methods will be studied, including those derived from topological algebra and those based on machine learning methods.

FAQ

FAQ – Your questions, Our answers

The thesis program is designed for students or graduates with a master’s or engineering degree who wish to extend their academic journey through research experience. It is particularly suited to those who want to gain an in-depth understanding of a subject, explore complex issues, and develop genuine scientific or technological expertise.

Not necessarily. A thesis can lead to a career in research, but that’s not the only path. Above all, it helps you develop strong skills in analysis, complex project management, working independently, and problem-solving. These skills are highly sought after in today’s business world, particularly in fields such as R&D, advanced engineering, and consulting.

Topics are determined in collaboration with partner laboratories and research teams. They address current scientific themes and feature a strong link between basic research and practical applications.

Yes. 3iL graduates are certainly able to pursue a Ph.D., depending on their goals and motivation. The school supports this process in collaboration with its partner laboratories and available research opportunities.

A doctoral dissertation opens up a wide range of opportunities. It can lead to a career in public or private research, in the R&D departments of innovative companies, or to positions as an expert engineer or project manager working on complex technical topics. It also serves as an excellent foundation for pursuing a career abroad or in higher education.