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Internship / Master's Thesis: Physics-Informed ML for Vehicle Dynamics Identification
München, DE, 80807
Live, first seen by us 15 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingReview physics-informed ML literature and evaluate vehicle dynamics modeling methods
Select approaches that minimize the simulation-to-reality gap
Implement, extend and optimize the selected methods
Validate models on synthetic and real-world datasets
Collaborate with pre-development and series development teams
From the employer’s posting
Review the state-of-the-art physics informed Machine Learning literature and evaluate methods for vehicle dynamics modeling
Evaluate and select suitable approaches to minimize the Simulation to Reality gap
Implement, extend, and optimize the selected methods
Validate the developed models using both synthetic and real-world datasets
Collaborate with teams in predevelopment and series development environments
What you’ll bring
All qualificationsCore experience
- Knowledge of control design and machine learning
- Experience with Python and machine learning frameworks such as PyTorch, etc.
- Hands-on experience through real-world projects, such as student projects, internships, or prior work experience
Preferred experience
- Physics-informed Machine Learning is a plus
Qualification wording
Knowledge of control design and machine learning (Physics-informed Machine Learning is a plus)
Experience with Python and machine learning frameworks such as PyTorch, etc.
Hands-on experience through real-world projects, such as student projects, internships, or prior work experience
Education & alternatives
- Collaborate with teams in predevelopment and series development environments - Work together with a PhD student in the field of Physics-informed Machine Learning and Simulation to Reality transfer WHO YOU ARE
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 20, 202615 days ago
- Recorded sightings
- 100
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Volkswagen is hiring
9 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is picking up
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- PyTorch
Where the posting names them
- Knowledge of control design and machine learning (Physics-informed Machine Learning is a plus) - Experience with Python and machine learning frameworks such as PyTorch, etc. - Hands-on experience through real-world projects, such as student projects, internships, or prior work experience
Your next step
Complete your application on jobs.volkswagen-group.com. The employer’s form will show what is required.
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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 TEAM
For the department Vehicle, Energy, Motion & Body (VEMB) we are looking for a student (intern or master thesis) for the project “System Identification with Physics-informed Machine Learning for Vehicle Dynamics”. 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
- Review the state-of-the-art physics informed Machine Learning literature and evaluate methods for vehicle dynamics modeling (e.g., SINDy, Symbolic Regression, etc.)
- Evaluate and select suitable approaches to minimize the Simulation to Reality gap
- Implement, extend, and optimize the selected methods
- Validate the developed models using both synthetic and real-world datasets
- Collaborate with teams in predevelopment and series development environments
- Work together with a PhD student in the field of Physics-informed Machine Learning and Simulation to Reality transfer
WHO YOU ARE
- Enrolled student in a relevant field such as Computer Science, Robotics, Electrical Engineering, or Mechatronics, with a strong focus on machine learning
- Knowledge of control design and machine learning (Physics-informed Machine Learning is a plus)
- Experience with Python and machine learning frameworks such as PyTorch, 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 hours/week
- Salary: 13,90 €/hour
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.
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- Pay
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- Location & working pattern
München, DE, 80807
NICE TO KNOW - Remote work options within Germany - Duration: 6 months
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.