PhD Candidate for Physics-informed Machine Learning in the context of Vehicle Models (f/m/d)

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!

YOUR TEAM

The aim of our PhD Program is to promote innovative topics that are relevant to CARIAD. We cooperate with top universities and bring new research projects to life. Our PhD candidates get the opportunity to create new innovations in their projects for CARIAD and the respective scientific field. All PhD projects are accompanied by a supervisor professor and a dedicated CARIAD mentor. Essential trainings for the PhD candidates complete the PhD Program.

For the department Vehicle, Energy, Motion & Body (VEMB) we are looking for a PhD candidate for the project “Learning Intelligent Onboard Functions”. Our department develops advanced software for vehicle energy, motion, and body systems. Our VEMB pre-development team works on methods for end-to-end learning of VEMB functions to enable faster, scalable and more cost-effective product development. We cover the entire development range—from initial concepts to proof of concepts in test vehicles in close cooperation with the series development departments.

WHAT YOU WILL DO

• PhD project with the working title: Physics-informed Machine Learning in the context of Vehicle Models
• Tackle key challenges in physics-informed machine learning with the focus on VEMB functions
• Review of the state-of-the-art in the subject area
• Embed physical knowledge in data-driven models, or vice versa, to take advantage of the physics-based model's interpretability and good generalization behavior, as well as the ability of machine learning to model complex data relationships
• Implement prototypes of developed algorithms and validate them experimentally in real world experiments 
• Collaborate with teams in pre-development and series development

WHO YOU ARE

• Master's degree in in a relevant field: Robotics, Electrical Engineering, Mechanical Engineering, etc
• Expertise in machine learning
• Very good programming skills in Python and/or C and experience with machine learning frameworks such as PyTorch, TensorFlow, etc
• Hands-on experience through real-world projects, such as student projects, internships, or prior work experience
• High level of commitment, initiative, and teamwork
• Good communication skills
• Fluent in English, German is a plus

NICE TO KNOW

• Duration: 3 years
• Working with high-ranked University
• Possibility to supervise students
• Remote work options
• Temporary work from abroad in selected countries
• 30 days paid leave
• Special Events e.g. PhD-Day (Doktorandentag), Trainings
• Note:Please attach a transcript of records including a module overview to your application via the system after you have submitted your application. Otherwise the application cannot be processed
• Important: The PhD admission requirements are set by the university and candidates have to fulfill these requirements before starting their projects. Candidates need a confirmation by the supervisor professor before onboarding (not necessary for application)
• If you have further questions about the candidate journey at CARIAD, please contact us: [email protected]

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 [email protected] - we are happy to support you.