PhD Candidate - Closed-loop RL with world models for E2E automated driving (f / m/d) | PhD students
München, DE, Berlin, DE, Wolfsburg, DE +1Основні характеристики вакансії
Дані: SQL / BI / Python
Сервер: Java / .NET / Node / Python
Працевлаштування: контракт
Віддалена робота - без поїздок
Повний робочий день
Description
We are CARIAD, the automotive software company of the Volkswagen Group. Our teams build automotive software platforms and digital customer functions for iconic brands like Audi, Volkswagen, and Porsche – supporting the Volkswagen Group in becoming the leading automotive technology company. With CARIDIANS in Germany, the USA, China, Estonia, and India, we are transforming automotive mobility for everyone. Join us and be part of this exciting journey! Note: please upload your transcript of records If you have further questions about the candidate journey at CARIAD, please contact us: careers@cariad.technology At CARIAD, we embrace individuality and diversity because we believe our differences make us stronger. We actively seek to build teams with a variety of backgrounds, perspectives, and experiences. Our goal is to create an environment where everyone feels valued and empowered to contribute. If you need assistance with your application due to a disability, please reach out to us at careers@cariad.technology – we are happy to support you. At CARIAD, we embrace individuality and diversity because we believe our differences make us stronger. We actively seek to build teams with a variety of backgrounds, perspectives, and experiences. Our goal is to create an environment where everyone feels valued and empowered to contribute. If you need assistance with your application due to a disability, please reach out to us at careers@cariad.technology - we are happy to support you.
YOUR TEAM
This PhD position offers the opportunity to conduct research on end-to-end networks for automated driving within our AI Core team. The project explores joint optimization of the driving stack by training perception, prediction, and planning within a unified model architecture, with emphasis on efficient training strategies, closed-loop evaluation, reinforcement learning, and integration with predictive world models. Our department develops software and machine learning models for automated driving in urban environments. You will work alongside experts in autonomous driving and artificial intelligence, contributing to state-of-the-art research and production-oriented AI systems in an agile, research-driven environment.
NICE TO KNOW
Duration: 3 years
Working with high ranked University
Remote work options
Possibility to supervise students
Temporary work from abroad in selected countries
30 days paid leave
Company
CARIAD SE
Contract
Fixed-term
Department
Research and Development
Shift
Full-time
Experience
PhD students
WHO YOU ARE
Excellent Master’s degree in Computer Science, Robotics, Mathematics, or a related field
Strong background in deep learning and modern machine learning methods
Solid understanding of computer vision, imitation learning, and reinforcement learning
Familiarity with world models, generative models, and autonomous driving is beneficial
Strong programming skills in Python, including PyTorch
Structured, independent, and research-oriented working style with above-average commitment
Strong communication skills and analytical understanding
Very good English communication skills
WHAT YOU WILL DO
Conduct research in machine learning and AI for automated driving
Explore novel approaches for end-to-end automated driving systems, including imitation learning, reinforcement learning, and world models
Investigate scalable and robust training strategies for autonomous driving applications
Work with modern deep learning architectures and large-scale datasets
Prototype, implement, and evaluate machine learning models on public datasets and benchmarks
Contribute to scientific publications and present research results
Collaborate closely with interdisciplinary research and engineering teams
Contribute to the development of next-generation automated driving technologies