MSc Control and Robotics Signal and Image Processing

Programme Objectives

The Signal and Image Processing Master's programme focuses on understanding and developing state-of-the-art methodology for data analysis, signal and image processing, and machine learning.

The acquired knowledge concerns both theoretical foundations and practical applications of data science and information retrieval, essential for the development of cutting-edge numerical methods. The courses delve into advanced data analysis techniques, encompassing computational statistics, applied mathematics, information theory, and scientific computing. Practical implementation is explored across various domains, including biomedical engineering, computational imaging, audio processing, industrial manufacturing, or remote sensing.
A distinguishing feature of the program lies in its emphasis on designing mathematical solutions tailored to the specificity of the data. Both model-based (taking into account physical models and sensing devices) and data-based (relying on statistical and deep learning) approaches are considered, ensuring that the numerical implementation aligns with the specific requirements of the application context, data volume, and available computational resources.
The programme of study lasts two academic years - denoted by M1 and M2 and is taught in English. It comprises three study semesters followed by a paid Master's thesis / internship in the final semester.
Our Master's programme in Signal and Image Processing is fully accredited by the French Ministry of Higher Education and Research.
Students applying for the Signal and Imaging Processing programme can also apply to join the Integrated Master-PhD track, which brings together the two years of the Master's degree and three years of PhD studies. The Integrated Master-PhD track is designed to give high-potential students exposure to research activities as soon as they join the M1 year.


Course Content

30 ECTS Credits per semester.
Language of instruction: English

M1 Year - 2024/25

* '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 - 2024/25

* '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

Examples of previous internships:

• * Analysis and visualization of physiological signals
• * Inverse problems for lens-free imaging of nanostructured surfaces
• * Survival analysis and graph representations
• * Early fusion of multiple MRI sequences for enhancing pathologic case retrieval systems in radiology
• * Coherence-based denoising for ultrasound small vessels imaging
• * Target detection and segmentation algorithm based on deep learning and application of big data technology in satellite remote sensing
• * Automatic reading recognition for pointer meters based on machine vision
• * Synthetic data generation for privacy purposes
• * Recognition of infrared protocols for AC systems using machine learning
• * 3D and 4D data processing with quaternion tensor decompositions
• * Simulation study of linearized weighted least square estimation for inverse polynomial model
• * Joint sparse decomposition of multivariate signals based on optimal transport

NB Internships undertaken in France are strictly regulated and are only open to current full-time students of an accredited educational institution. Interns are entitled to all the rights guaranteed to regular employees (such as social protection and redress mechanisms). For internships that exceed two months in duration a minimum level of remuneration is set by the government, at approximately €600 per month. In some professional branches, this amount may be higher.

Skills Developed

• Understand the basic concepts underlying modern data processing methods (assumptions, limitations)
  ► Informed user: make the best choice for analyzing a given data set (choose a method, set the parameters, implement)
• Master the fundamentals and identify how advanced data processing knowledge can raise new challenges
  ► Research: develop novel methodological tools and make scientific progress
• Acquire a solid background on real-life applications of signal and image processing in research and innovation
• Be aware of latest trends in AI-based techniques and become an expert in data science

In addition to the above specialism-specific skills, students will also develop more general skills:

• * Identify models, perform simulations and analyse results
• * Undertake a literature survey of existing works on a scientific problem
• * Communicate comprehensive results in a meaningful way
• * Manage and supervise research and innovation projects