BMW Group

PhD AI Driven Crash Simulation and Geometric Deep Learning (f/m/x)

Stellenbeschreibung:

PhD Position: AI-Based Crash Predictions

Our ProMotion PhD programme offers you the opportunity to apply your passion and scientific expertise to real challenges that could shape the future of mobility.

Responsibilities

  • 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 AI models for CAx applications in the crash design process for cars.

Qualifications

  • 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, or Transformer 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.

Benefits

  • 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:

Duration: 36 months

Working hours: Part‑time

At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants.

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Stelleninformationen

  • Veröffentlichungsdatum:

    15 Apr 2026
  • Standort:

    München

    Einsatzort:

    Munich, Germany
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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