General information
Organisation
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
Reference
2025-37663
Description de l'unité
The mission of the Intelligent Integrated Multi-Sensor Laboratory (LIIM) is to study and develop embedded algorithms in the domains of artificial intelligence, data fusion, and environment perception for multi-sensor cyber-physical systems. It also focuses on designing and implementing software and hardware demonstration platforms that utilize these algorithms, incorporating innovative technologies, especially for the creation of specific integrated circuits
Position description
Category
Mathematics, information, scientific, software
Contract
Internship
Job title
Classification of objects from RADAR data for automotive applications
Subject
The objective of the internship is to utilize RADAR data from public datasets (KRADAR, RADIAL) to develop classification techniques for identifying various road users (such as other vehicles, cyclists, and pedestrians) as well as static obstacles (including road infrastructure and objects on the road). The intern will focus on innovatively processing RADAR data using an existing framework developed within the laboratory. The task includes extracting parts of the RADAR data (RADAR cubes) to perform classification exclusively on areas of interest. By extracting these cubelets, the aim is to reduce the size of the neural networks employed. The primary challenge of this internship will be to optimize the processing and extraction of RADAR information from these cubelets to achieve the highest possible accuracy.
Contract duration (months)
6
Job description
The Technological Research Direction (DRT) of the CEA aims to develop innovative solutions and interact with industrial partners to valorize these innovative technologies. The LIIM laboratory (Intelligent Integrated Multi-Sensor) has expertise in environmental perception through its knowledge of various sensors (Camera, LIDAR, RADAR, Infrared) applied to different fields such as automotive, robotics, and drones. Within a multidisciplinary team of research engineers, your role will be to participate in the design of AI algorithms using RADAR data. The internship will focus on developing AI tools to improve the quality of classification algorithms on RADAR data. This work is intended to be presented to industrial partners and may be the subject of scientific publications.
In collaboration with the team's researchers, the main task will be to improve the existing AI algorithms within the laboratory. This work must take into account the specificities of RADAR data and improve the processing and extraction of cubelets. The intern must demonstrate critical thinking and will need to define and implement key metrics to determine the quality of the proposed solution. In a second phase, the work will consist of finding the best compromise between the size of the cubelet data, inference time, and the quality of the solution. Part of the work will involve presenting and highlighting the results of the internship, particularly by participating in the writing of scientific publications.
Methods / Means
AI/Python/Pytorch
Applicant Profile
Required Skills and Qualifications:
Proficiency in Python
Knowledge of artificial intelligence and PyTorch
Experience with RADAR and signal processing is a plus
Desired Qualities:
Ability to work in a team and communicate results clearly
Sensitivity to the research environment
Autonomy and proactivity
Position location
Site
Grenoble
Job location
France, Auvergne-Rhône-Alpes, Isère (38)
Location
Grenoble
Candidate criteria
Prepared diploma
Bac+5 - Master 2
Recommended training
M2
Requester
Position start date
01/02/2026
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