PhD- Virtual Reliability Assessment: New Methods for Leveraging the Simulation Chain

Bosch Group; Renningen; Hybrid; EUR 60.000 - 90.000; Vollzeit

Zusammenfassung

An innovative company is seeking a talented researcher to contribute to groundbreaking work in lifespan prediction of components. This role involves developing advanced simulation methods, leveraging AI technologies, and conducting fundamental research that will shape the future of engineering. The ideal candidate will possess a strong background in engineering or computational sciences, along with proficiency in Python programming. Join a dynamic team that values diversity and offers flexible working models, ensuring a collaborative environment where your contributions will make a significant impact.

Qualifikationen

• Above average degree in relevant engineering or science fields.
• Experience in simulation methods and AI frameworks.

Aufgaben

• Conduct scientific research on lifespan prediction of metallic components.
• Develop DoE models and implement AI approaches using Python.

Kenntnisse

Python

Simulation methods

Design of Experiments (DoE)

AI/LLM approaches

Numerical implementation

Ausbildung

Mechanical Engineering

Applied Maths

Physics

Computer Science

Computational Science and Engineering

Jobbeschreibung

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: We grow together, we enjoy our work, and we inspire each other. Welcome to Bosch.

The Robert Bosch GmbH is looking forward to your application!

Job Description

• You will conduct fundamental scientific research (PhD) that makes a significant contribution to predicting the lifespan of metallic components and more.
• In addition, you will develop Design of Experiments (DoE) models for the analysis and synthetic generation of virtual load collectives.
• Furthermore, you will also research the question of how LLM-based multi-agent systems perform in the selection of input data for the simulation chain and how effectively multi-agent systems can serve as developers of tools for reliability simulations.
• Also, you will implement data-based and AI/LLM approaches using Python code.
• You will also develop methods to evaluate the quality of results / uncertainties and apply the methods to a demonstrator system.
• Last but not least, you will implement an existing software platform.

Qualifications

• Education: above average degree in Mechanical Engineering, Applied Maths, Physics, Simulation Technology, Computer Science or Computational Science and Engineering
• Experience and Knowledge:
  • advanced knowledge and experience in the development of simulation methods for engineering problems
  • good knowledge in the field of computational lifespan estimation of components and systems as well as in the areas of Design of Experiments (DoE) methods and AI agentic frameworks
  • Experience in data-based or hybrid modeling and implementation in Python program code as well as in the numerical implementation of models
• Personality and Working Practice: your proactive and committed attitude makes you a valued team member; you never lose sight of your goals and you are comfortable presenting and speaking in front of others
• Languages: very good in German and English

Additional Information

https://www.bosch-ai.com
www.bosch.com/research

The final topic depends on your university.

Start: by prior agreement

We offer flexible working models: from various part-time options to mobile working and job sharing. Feel free to contact us.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need support during your application?
Sarah Schneck (Human Resources)
[phone]

Need further information about the job?
Benjamin Maier (Functional Department)
[phone]