Company AMPERE SOFTWARE TECHNOLOGY Job Description Thesis subject description Autonomous driving is inherently a geometric problem, where the goal is to identify and understand the scene (road agents, context …) and to navigate a vehicle safely and correctly through 3D space. As sensor configurations get more complex, integrating multi-source information from different around view cameras and representing features in a unified view come of vital importance. The core subject of this PhD is to study and develop innovative concepts, algorithms and methods to enhance situational awareness of autonomous systems in dynamic environments using spatio-temporal Artificial Intelligence. The overall aim of this research will be a vehicle perception system that is capable of detecting, tracking and understanding the entire environment surrounding a car, navigating in complex conditions ranging from dense urban scenarios to country road with varying weather conditions using a Bird’s-eye-view (BEV) end-to-end perception framework. BEV perception inherits several advantages, as representing surrounding scenes in BEV is intuitive and fusion-friendly; and representing objects and/or road elements in BEV is most desirable for subsequent modules as in planning, trajectory forecasting and/or control. The PhD subject will explicitly address the following topics: 3D object detection, semantic segmentation, drivable space, and multi-agent dynamics by predicting multi-hypothesis future instance segmentation and motion in BEV representation. The main research axes of this thesis can be broken into the following main tasks. Task 1. Scene understanding: The goal is to develop new camera-based perception algorithms including semantic segmentation and depth maps topics (i.e., 3D objects and lanes detection). Deep learning approaches have shown good results when applied to these topics and will be investigated. Task 2. Predict long-term situation awareness by considering the future interactions of the dynamic agents in the scene. A probabilistic approach will predict plausible and multi-modal futures of the dynamic environment integrating the others agent’s intentions and the context. Task 3. Computation complexity: Explore the ways to encode the multi-view image features into a compact latent space. Decoupled it from the input size and output resolution, enabling precise computational budget control. Academic partner: I3S laboratory at Sophia-Antipolis Your missions A PhD thesis allows you to develop multiple skills to enable you to carry independent research, at the same time we develop the know-how on key technologies.  You shall have the opportunity to formulate novel solutions whilst making the most of our prototype platforms.  You will need to gain a strong understanding of computer vision and principles of machine learning from the vehicle navigation perspective and gain critical thinking to formulate the problem, propose solutions, and test them. Your profile You should be completing or have Bac+5 level degree, an engineering diploma or a Master 2 in Computer Science, Computer Vision, Robotics or Signal Processing. You are very much interested in the automotive domain and the use of perception systems. It is very important to be curious, willing to learn new techniques. You will have the opportunity to formulate your own ideas, to test them in the Renault prototype vehicles. Experience with image and signal processing, fundamentals of machine learning, programming (C++, Python language), robotics technologies. A working knowledge of the English language is required. Job Family Research & Development Contract Duration 36 months Renault Group is committed to creating an inclusive working environment and the conditions for each of us to bring their passion, perform to the full and grow, whilst being themselves.   We find strength in our diversity and we are engaged to ensure equal employment opportunities regardless of race, colour, ancestry, religion, gender, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, etc. If you have a disability or special need requiring layout of the workstation or work schedule, please let us know by completing this form. In order to follow in real time the evolution of your applications and to stay in touch with us, we invite you to create a candidate account. This will take you no more than a minute and will also make it easier for you to apply in the future. By submitting your CV or application, you authorise Renault Group to use and store information about you for the purposes of following up your application or future employment. This information will only be used by Renault Group companies as described in the Group privacy policy.

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Renault

PhD thesis at AMPERE SOFTWARE TECHNOLOGY in collaboration with I3S laboratory to enhance autonomous systems' situational awareness using AI. Involves developing algorithms for scene understanding, predicting interactions, and managing computational complexity.

PhD Thesis CIFRE "Bird’s-Eye View: Contextual scene understanding from Around View Monitoring Cameras" (H/F)

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