PhD AI Driven Crash Simulation and Geometric Deep Learning

BMW AG
München, Germany
19 days ago

Role details

Contract type
Temporary contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English, German

Tech stack

Computer-Aided Design Artificial Intelligence Artificial Neural Networks Machine Learning Deep Learning Information Technology Data Analytics

Job description

To strengthen our team in München we are looking for a/an PhD AI Driven Crash Simulation and Geometric Deep Learning (f/m/x) Our brands BMW, MINI, Rolls-Royce and BMW Motorrad have made us one of the world’s leading premium manufacturer of cars and motorcycles as well as provider of premium financial and mobility services. THE FUTURE IS WHAT WE CREATE WHEN WE TAKE OUR VISIONS TO THE LIMITS. PHD AT THE BMW GROUP. Bridging the gap between your doctoral studies and the kind of career challenge you’re looking for isn’t always easy. That’s why our ProMotion PhD programme gives you the opportunity to apply your passion and scientific expertise to very real challenges that could shape the future of mobility. If selected, you’ll have the chance to really develop your own future career path with us through your practice-related thesis, promote your chosen specialty from within - and position yourself to secure the career you’ve always wanted. We are offering an exciting PhD position focused on AI-based crash predictions using 3D crash simulation techniques. The successful candidate will contribute to the development of innovative AI models and data-driven methods to improve the accuracy and efficiency of crashworthiness assessments in automotive safety engineering.What awaits you? Develop AI models for vehicle crash behavior using modern geometrical AI architectures Integrate machine learning and data analytics approaches with physics-based simulations to improve prediction accuracy. Contribute to the development of automated workflows and optimization methods for crash simulations. Research in AI models for CAx (CAD, CAE etc.) applications in crash design process for cars What should you bring along? University degree in engineering, computer science, mathematics, or an equivalent field. Experience in AI model development with a focus on geometrical deep learning, e.g. Graph Neural Networks, Geometric Transformers, Transolver architectures. Good understanding of CAx artifacts (3D geometry, simulation model, etc.) and related workflows used in product design and development. Solid background in numerical simulations, particularly with transient schemes. A track record of research contributions (publications, conference talks, or equivalent) is a plus. Business-fluent English; German language skills are a plus. Are you motivated and keen to help us shape the mobility of tomorrow? Apply now!Find out more about Artificial Intelligence at the BMW Group here. Note: Please apply exclusively online through our career portal. Applications submitted via other channels (including email) cannot be considered. Citizens of countries outside the European Union must have a valid residence or work permit for the duration of the program. What we offer? Comprehensive mentoring & onboarding. Personal & professional development. Flexible working hours. Digital offers & mobile working. Attractive & fair remuneration. Annual special payments such as vacation pay and Christmas bonus. Apartment offers for students (subject to availability & only Munich). And many other benefits - see bmw.jobs/benefits Earliest starting date: 01.05.2026 Duration: 36 months Working hours: Part-time Job ID: 182014 BMW Group Recruiting Munich APPLY NOW Are you looking for an exciting challenge? Then join our team. You can find detailed information about us at bmwgroup.jobs/careers More Insights also on Instagram and Facebook @bmwgroupcareers

Requirements

on AI-based crash predictions using 3D crash simulation techniques. The successful candidate will contribute to the development of innovative AI models and data-driven methods to improve the accuracy and efficiency of crashworthiness assessments in automotive safety engineering.What awaits you? Develop AI models for vehicle crash behavior using modern geometrical AI architectures Integrate machine learning and data analytics approaches with physics-based simulations to improve prediction accuracy. Contribute to the development of automated workflows and optimization methods for crash simulations. Research in AI models for CAx (CAD, CAE etc.) applications in crash design process for cars What should you bring along? University degree in engineering, computer science, mathematics, or an equivalent field. Experience in AI model development with a focus on geometrical deep learning, e.g. Graph Neural Networks, Geometric Transformers, Transolver architectures. Good understanding of CAx artifacts (3D geometry, simulation model, etc.) and related workflows used in product design and development. Solid background in numerical simulations, particularly with transient schemes. A track record of research contributions (publications, conference talks, or equivalent) is a plus. Business-fluent English; German language skills are a plus. Are you motivated and keen to help us shape the mobility of tomorrow? Apply now!Find out more about Artificial Intelligence at the BMW Group here. Note: Please apply exclusively online through our career portal. Applications submitted via other channels (including email) cannot be considered. Citizens of countries outside the European Union must have a valid residence or work permit for the duration of the program. What we offer? Comprehensive mentoring & onboarding. Personal & professional development. Flexible working hours. Digital offers & mobile working. Attractive & fair remuneration. Annual special payments such as vacation pay and a

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.jobstairs.de

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:21 min

Introduction to machine learning in the automotive industry

Jan Zawadzki · LIVE

1:25 min

Distinguishing artificial intelligence from deep learning

Sam Witteveen · Coffee With Developers

1:32 min

Structuring platforms for new services and data analytics

Nevelina Aleksandrova · LIVE

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

3:51 min

Overcoming hardware configuration barriers in machine learning

Jose Luis Latorre Millas · LIVE

3:01 min

Transitioning into the automotive artificial intelligence safety field

Tillman Radmer +2 · WWC 2021

Videos

See all

Related articles

See all