Onsite PhD, AI Framework for Data-Driven Product Innovation

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About the role

  • Engage in a three-year PhD program focused on developing AI frameworks to enhance automotive product innovations. Collaborate with industry partners and research institutions in advanced engineering.

Responsibilities

  • A three-year, individually designed doctoral (PhD) program within the Group’s Advanced Engineering department
  • PhD research program in AI frameworks for multi-source data integration to support product innovations in automotive development
  • Development of a scalable AI framework that integrates internal data (production, sales, after-sales feedback) with external sources (social media, online communities, market APIs, IoT telemetry, partner data)
  • Application of methods such as predictive analytics (e.g., preventive failure prediction), white-spot identification (detecting innovation gaps), and digital product innovation
  • Intensive research and development activities in close collaboration with industry partners and research institutions

Requirements

  • Excellent university degree (Master’s or equivalent) in Computer Science, Data Science, Business Informatics, or a related field with a focus on AI / Machine Learning
  • Strong knowledge of artificial intelligence, databases, and data analysis
  • Experience in innovation management, particularly in identifying innovation gaps (white spots) to predict risks and improve products
  • Excellent English and fluent German language skills
  • Ability to work independently in a scientific environment, flexibility, teamwork skills, structured thinking, and a strong commitment

Benefits

  • Professional supervision from the specialist department
  • Talent development programs
  • Early discussions about potential career opportunities within the company

Job title

PhD, AI Framework for Data-Driven Product Innovation

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

Postgraduate Degree

Tech skills

Location requirements

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