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Sie haben ein erfolgreich abgeschlossenes Hochschulstudium (Master oder vergleichbar) im technischen Bereich (bspw. Maschinenbau, Elektrotechnik,…
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You will develop Python-based data pipelines for the automated extraction and processing of EDU data from vehicle databases
You will use generative AI and large language models (LLMs) to intelligently estimate bills of materials (BoMs) for electric powertrains based on existing vehicle parameters
You will develop prompt and tool-calling strategies for AI-assisted prediction of technical component and material data
You will integrate the generated BoM data into LCA models and automate the calculation of CO₂ footprints and environmental impacts
You will validate the results using real vehicle data and optimize the accuracy and robustness of the AI models
You will work on an innovative, data-driven engineering pipeline from requirements definition to automated sustainability assessment

You are a enrolled bachelor or master’s student (m/f/d) in mechanical engineering, automotive engineering, computer science, electrical engineering, or a comparable field of study
You have strong programming skills in Python
You excel at analytical and logical thinking and are able to work independently
You are passionate about modern AI technologies and their application in engineering
You have a basic understanding of electric powertrains (EDU) and their components
Ideally, you have some experience developing applications using Large Language Models (LLMs) and generative AI
Preferably, you have a basic understanding of working with databases (e.g., SQL)
Ideally, you have a basic understanding of Life Cycle Assessment (LCA) and sustainability assessment