PhD candidate working on AI regression models for crash design in collaboration with BMW Group. Engaging in data analysis and model development to enhance vehicle safety protocols.
Responsibilities
Support comprehensive analysis and preprocessing of large-scale simulation data, including curves and scalar values
Help to develop and train a Foundation Model using the entire database of passive safety simulation data
Research state-of-the-art possibilities for an interface that enables users to interact with the foundation model
Contribute to close collaboration with passive vehicle safety experts to validate and refine the model and application
Assist in preparing and presenting research findings for scientific journals and conferences, advancing vehicle passive safety and data-driven modeling
Requirements
Studies in computer science, data science, mechanical engineering or mathematics
Strong background in machine learning, with experience in neural network architectures and regression modeling; experience with large-scale foundation models is a plus
Familiarity with programming languages and tools for data processing, model development, and integration (e.g., Python, TensorFlow)
Experience in handling large-scale simulation databases and extracting relevant training data
Excellent analytical and problem-solving skills to address complex engineering challenges
Creativity and innovation to explore novel approaches and extend existing methods
Strong written and oral English skills
Benefits
Comprehensive mentoring & onboarding
Personal & professional development
Flexible working hours
Digital offers & mobile working
Attractive, fair remuneration
Apartment offers for students (subject to availability & only Munich)
Job title
PhD, Generic AI Regression Models for Early Phase Crash Design
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