Internship / Masters Thesis – Physics-informed Machine Learning for Vehicle Functions (f/m/d)

Job title: Internship / Masters Thesis – Physics-informed Machine Learning for Vehicle Functions (f/m/d)

Company: Volkswagen


Job 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!YOUR TEAMFor the department Vehicle, Energy, Motion & Body (VEMB) we are looking for a student (intern or master thesis) 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

• Work together with a PhD student in the field of physics-informed machine learning with the focus on VEMB functions
• Review of the state-of-the-art in the subject area
• Help in embedding 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
• Assist in implementing prototypes of developed algorithms and validate them experimentally in real world experiments
• Collaborate with teams in pre-development and series development

WHO YOU ARE

• Enrolled student in the a relevant field: Robotics, Electrical Engineering, Mechanical Engineering, etc.
• Knowledge in control design and/or machine learning, e.g Reinforcement Learning or Physics Informed Machine Learning
• Experience with in Python and 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
• Strong analytical and problem-solving skills
• High level of commitment, initiative, and teamwork
• Fluency in English and German and good communication skills

NICE TO KNOW

• Remote work options within Germany
• Duration: 6 months
• 35-hour week

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 – we are happy to support you.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 TEAMFor the department Vehicle, Energy, Motion & Body (VEMB) we are looking for a student (intern or master thesis) 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

• Work together with a PhD student in the field of physics-informed machine learning with the focus on VEMB functions
• Review of the state-of-the-art in the subject area
• Help in embedding 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
• Assist in implementing prototypes of developed algorithms and validate them experimentally in real world experiments
• Collaborate with teams in pre-development and series development

WHO YOU ARE

• Enrolled student in the a relevant field: Robotics, Electrical Engineering, Mechanical Engineering, etc.
• Knowledge in control design and/or machine learning, e.g Reinforcement Learning or Physics Informed Machine Learning
• Experience with in Python and 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
• Strong analytical and problem-solving skills
• High level of commitment, initiative, and teamwork
• Fluency in English and German and good communication skills

NICE TO KNOW

• Remote work options within Germany
• Duration: 6 months
• 35-hour week

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 – we are happy to support you.Job ID: 16356Company: CARIAD SELocation:Mönsheim, DE, 71297Department: Apprenticeship & StudyCareer Level: StudentsWorking Model: Full-timeContract Type: Fixed-termRemote Working: By agreementPosting Date: Jul 17, 2025Why CARIAD?We believe that how we work together is just as important as the technology we create. We strive to take action with a can-do attitude, and value speed over perfection. We aim to collaborate with mutual trust, taking accountability for our actions. We foster transparency and welcome diverse perspectives as we learn, adapt, and grow togetherMore informationHR contactDo you have any suggestions or questions? ✉️Legal Notices

Expected salary:

Location: Deutschland

Job date: Sat, 19 Jul 2025 04:02:55 GMT

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