PhD Position in Reinforcement Learning for Automated Driving
il y a 2 semaines
Context and Advantages of the Position
We are seeking a highly motivated PhD student to join our team at INRIA, working on the development of reinforcement learning-based decision-making and planning frameworks for automated driving systems. This project aims to advance the state-of-the-art in autonomous vehicle technology, focusing on safety, efficiency, and adaptability.
Research Objectives
The PhD thesis will focus on the following research objectives:
- Develop an RL-based decision-making and planning framework for automated driving systems, leveraging the Markov Decision Process and other relevant techniques.
- Optimize driving policies using RL algorithms to ensure safety, efficiency, and adaptability, building on recent studies that have demonstrated the effectiveness of RL in safe autonomous driving.
- Evaluate the performance of the proposed RL system through simulations and real-world testing, creating diverse driving scenarios and integrating the RL algorithm into a simulation/testing environment.
Main Activities
The successful candidate will be involved in:
- Research and development of RL-based decision-making and planning frameworks for automated driving systems.
- Writing scientific papers and presenting work at conferences.
- Programming and data management.
- Interacting with partners and collaborators.
- Participating in demonstrations and showcases.
Candidate Profile
We are looking for a candidate with a strong background in machine learning, particularly reinforcement learning, and proficiency in programming languages such as Python and C++. The ideal candidate should have a solid understanding of robotic systems and control challenges, as well as experience in developing control algorithms or motion planning strategies for autonomous vehicles.
Language and Additional Skills
The candidate should have a good level of English for communication and be familiar with automated vehicles simulation environments. Additional skills, such as strong problem-solving skills, ability to work independently and collaboratively, and autonomy, are highly desirable.
Benefits
The successful candidate will benefit from:
- Subsidized meals.
- Partial reimbursement of public transport costs.
- Leave and flexible organization of working hours.
- Professional equipment and access to vocational training.
- Social security coverage.
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