Integrated Master-PhD Track | Data Science, Signal and Image Processing

The Integrated Master-PhD Track is available in Data Science, Signal and Image Processing.

Students on the track will be assigned to the Laboratory of Digital Sciences of Nantes (LS2N) with supervision from a member of faculty. It is within LS2N Laboratory that the students on this track would naturally progress towards funded PhD studies, subject to successful completion of the Master's degree, final acceptance by the ad hoc committee and the award of a PhD grant.

Course Content

Course content in the M1 and M2 years is based on the Master's specialism - Data Science, Signal and Image Processing - whereby Integrated Master-PhD Track students have a (limited) choice of modules, plus a research module and supervised research project. Full details below.

Data Science, Signal and Image Processing

M1 Year

30 ECTS Credits per semester.
Language of instruction: English
 

Autumn Semester 2025-26

Core Courses	ECTS
Algorithmics and programming	4
Artificial Intelligence	6
Classical Linear Control	5
Mathematical Tools for Signals and Systems	4
Embedded Computing	4
Signal Processing	5
Language Courses (1 out of 3)*
French as Foreign Language	2
Cultural and Communicational English	2
Spanish	2

* 'French as Foreign Language' except for French native speakers who will study 'Cultural and Communicational English' or Spanish (depending on sufficient demand).

In addition to the courses, students will attend scientific seminars to gain an overview of research activities in the field of control and robotics. This will enable them to identify the areas in which they wish to focus their research activities for the remainder of the programme.
 

Spring Semester 2025-26

Core Courses	ECTS
Research project	6
Computer Vision	4
Image Processing	5
Optimization Techniques	5
Systems Identification and Signal Filtering	4
Spectral and Time Frequency Analysis	4
Language Courses (1 out of 3)*
French as Foreign Language	2
Cultural and Communicational English	2
Spanish	2

* 'French as Foreign Language' except for French native speakers who will study 'Cultural and Communicational English' or Spanish (depending on sufficient demand).

NB Course content may be subject to minor changes

M2 Year

30 ECTS Credits per semester.
Language of instruction: English
 

Autumn Semester 2025-26

Core Courses	ECTS
Advanced Research project	8
Elective Courses (choose 5 out of 6)
Biomedical signals, images and methods	4
Design of signal and image representations	4
Machine learning, data analysis and information retrieval	4
Mathematical tools for signal and image processing	4
Signal and image restoration, inversion methods	4
Stochastic methods	4
Language Courses (1 out of 3)*
French as Foreign Language	2
Cultural and Communicational English	2
Spanish	2

* 'French as Foreign Language' except for French native speakers who will study 'Cultural and Communicational English' or Spanish (depending on sufficient demand).
 

Spring Semester

	ECTS
Master Thesis/Internship	30

NB Course content may be subject to minor changes

Download syllabus | Integrated Master-PhD Track - Data Science, Signal and Image Processing

• M1 Year
• M2 Year

 

Research Environment

This programme relies on Centrale Nantes’ faculty and the research facilities of the Laboratory of Digital Sciences of Nantes (LS2N).

About the LS2N

The LS2N Laboratory was launched with a single objective: bring together Nantes' research expertise in computer science and cybernetics to develop digital sciences, inclusive of other disciplines and taking account of the social challenges involved. The five areas of research expertise:
 

• Industry of the future | systems engineering, control, human factors, management, software engineering, robotics
• Management of energy and environmental impact  | embedded systems design, eco-design of robots, power grids, adaptable data centres
• Life Sciences  | medical imaging, neuronal signal processing, genomic data analysis,  biological network modelling, artificial organ design, automation of hospital equipment
• Vehicle and mobility | global vehicle automation, behavioural and usage modelling, traffic optimization
• Design, culture and digital society  | system design for the digital society, design of new interactions and links with digital artefacts, analysis of practices and interaction with digital artefacts

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Major Research Projects

MILCOM - Develop machine learning methods for the acquisition, annotation and analysis of medical images

The MILCOM project combines data sciences and health, and focuses on the application of machine learning to analyse multimodal medical images for the validation and identification of biomarkers in oncology.
The research work is being carried out by a multidisciplinary team from the LS2N, in collaboration with the Nuclear Medicine Department at Nantes University Hospital and the CRCINA team at Inserm, and is supervised by Diana Mateus, professor at Centrale Nantes and member of the Signal, Image and Sound (SIMS) team at LS2N.
The project aims to develop machine learning methods for the acquisition, annotation and analysis of medical images to assist doctors in their decision-making. Ultimately, the MILCOM project should help oncologists to diagnose and provide personalised treatment for patients suffering from diseases such as multiple myeloma.

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OWL (Operating Within Limits)  - Develop new algorithms for circadian AI

The OWL Project proposes a new model of computation for more frugal intelligent autonomous sensors: circadian artificial intelligence (AI). The targeted applications are in the field of environmental monitoring, especially bioacoustic and its application in conservation ecology.  This model is particularly well suited for sensors without batteries that are intermittently powered by ambient energy. The great promises of these systems is the extension of their lifetime without the need for human intervention allowing for long-term biostatistics observation missions, and a lower impact on the environment thanks to the absence of battery.
Circadian AI is interested in observing phenomena that have a period of one day, such as the activity of birds or the pollution associated with traffic in a metropolis. It exploits the fact that this period is shared with the availability of solar energy, which is used to power the sensors. This correlation allows the systems to temporally shift the costly computations required to perform the AI functions to times when the observed phenomenon is at rest and energy is abundant.
The project proposes two main contributions. The first is to propose new algorithms for circadian AI that allows for this temporal shift in computation. The second is to provide the software and hardware infrastructure necessary to run circadian AI on intermittently powered sensors.
OWL is funded by the French National Research Agency as part of the Specific Topics in Artificial Intelligence (TSIA 2023) programme.

Research Facilities

The "Autonomous Vehicles" research facility allows the LS2N to integrate and evaluate the approaches under development in autonomous mobile robotics around the themes of environment perception, understanding of scenarios and multi-sensor referenced control. The platform includes 3 instrumented vehicles (sensors, computers and man-machine interfaces), 2 of which are fully robotized by the "Drive-by-wire" robotization kit developed by the ARMEN research group in the LS2N.

As part of an industrial research chair with Renault, which aims to improve the performance of electric propulsion in motor vehicles, Centrale Nantes has an electric vehicle test bench specifically for automotive electric propulsion. It comprises of test engines supplied by Renault and a control, power electronics and dynamic load environment to simulate driving situations.

PhD Opportunities

• Fast ultrasound imaging methods for non-destructive testing of attenuating and scattering materials
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• Analysis and synthesis of urban sound scenes using deep learning techniques
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• Deep learning for computer-aided early diagnosis of breast cancer
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• Probabilistic models based on EMG decomposition for prosthetic control
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• On-line decomposition of iEMG signals using GPU-implemented Bayesian filtering
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• Improvement of the quantification of yttrium-90 PET images
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What our students and graduates say

Osimone, PhD Student 2023-2026 | MSc Signal and Image Processing, Class of 2022

Video Transcript

My PhD Story: by Osimone, Master SIP, PhD LS2n Laboratory

Hello everyone. I'm Osimone. I'm a first-year doctoral student at LS2N in Centrale Nantes. I am Nigerian and I initially did my bachelor's degree in Nigeria in Electronics Engineering at Convenant University. I came here to do my Master's degree in Signal and Image Processing. After that, I was a research engineer for a while at the LS2N also, and then I started my doctoral studies. 

Why did you decide to come to Centrale Nantes? 

I've always been interested in signal processing and artificial intelligence, so I was looking for a course that taught those lines. After seeing some of the courses or programmes provided by Centrale through a scholarship scheme in Nigeria, I decided to apply. For a long while, before even these opportunities were made available, I wanted to come to France. So that's one of the reasons I chose Centrale and I saw that it was one of the best universities in France. 

When and why did you decide to pursue you PhD here? 

So, for a long while I've wanted to do a doctoral degree. After finishing my Master's degree, my supervisor who I worked with during my Master's degree proposed a wonderful subject that towed the lines of artificial intelligence and signal processing, so I decided to do a PhD. Another thing is I love the city of Nantes! 

What are you working on for your PhD? 

For my PhD I'm working on a digital twins. It's basically the virtual replica of a physical system in the virtual domain. The reason we are applying it is for a thermo-hydraulic system for predictive maintenance and supervision and it tows the line of signal processing and artificial intelligence, and that's the reason I chose it. 

How would you rate the research facilities and support?

Here at Centrale, I'd rate the support and resources as top-notch and world-class because there's provision for everything that's necessary and needed: technical resources, the support from even fellow doctoral students, from the professors ... all that's needed is available, and so I rate it highly. 

What are your plans for the future? 

For my future I'm interested in several fields. I'm looking for ways I can apply the studies I'm doing on digital twins in a plethora of fields, like the automobile industry, the aviation industry, and even in music. If I can do it in music, I'll be very happy! 

Any advice for future applicants? 

You should know what you are interested in, know how your interests align and choose a subject - Master's thesis or PhD - in that line. Seek advice from people in the field and that will help you. 

Centrale Nantes in 3 words?

Accommodating - Innovative - Diversity

Yuxin, PhD Student 2021-2024 | MSc Signal and Image Processing, Class of 2021

Why did you decide to come to Centrale Nantes for your MSc Programme in Signal and Image Processing?

"During my final undergraduate year, I was an exchange student at ECN, where I discovered it to be an excellent choice, both for its quality of life and academic offerings. As I reconsidered my original major and contemplated a switch, ECN provided a relaxed environment for me to weigh my options and explore various fields. Ultimately, I found that signal and image processing aligned best with my interests."

When and why did you decide to pursue your PhD here?

"During the final semester of my master's program, my laboratory internship provided me with a preliminary insight into the world of research. It was during this time that I developed a keen interest in the field of medical imaging. Motivated by the desire to delve deeper into this domain and experience the authentic lifestyle of a researcher, I decided to pursue a Ph.D. program."

What are you working on for your PhD?

"For my Ph.D., I am engaged in research on 'Medical Ultrasound Imaging with Deep Learning'. This involves exploring innovative applications of deep learning techniques in the realm of medical ultrasound imaging."

How would you rate the research facilities and support?

"Our laboratory LS2N is well-equipped with the necessary machinery and facilities for experiments. We maintain a close relationship with the companies that provide the machines. In terms of computational resources for deep learning, besides the GPU available on my workstation, we also have access to a high-performance computing cluster."

What do you plan to do after graduation?

"After graduation, I hope to join a company specializing in medical ultrasound imaging, where I can actively contribute by addressing specific challenges and solving real-world problems for end-users."

Any advice for future applicants?

"I advise prospective applicants to identify their genuine interests and suitable pursuits as early as possible. When considering an application, it's crucial to gather comprehensive information, including course structures, graduation requirements, and employment prospects. Ideally, early awareness of the core competencies each program cultivates can guide applicants in making informed choices that align with their future goals."

Meet the Programme Coordinator

Pierre-Emmanuel Hladik is an Assistant Professor at Centrale Nantes and he carries out his research activity at the Laboratory of Digital Sciences of Nantes (LS2N) in the STR team. He previously spent 14 years in Toulouse at the Laboratory of Architecture and Analysis of Systems (LAAS-CNRS). He teaches in the field of autonomous embedded systems. His research interests deal with the modelling and verification of constraint concurrent systems, and in particular scheduling and methods to design safe systems.

There is no need to apply for the track before arriving at Centrale Nantes for your Master's programme. Your choice will be taken into account during the first year of the Master's programme so as to orient your laboratory research activities and the choice of elective modules towards the PhD thesis subject.