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- Aufgaben: Conduct groundbreaking research on predicting lifespan of metallic components and develop innovative simulation methods.
- Arbeitgeber: Join Bosch, a leader in high-quality technology and services that enrich lives.
- Mitarbeitervorteile: Enjoy flexible working models, including remote work options and a supportive team culture.
- Warum dieser Job: Be part of a dynamic team that values innovation, collaboration, and personal growth.
- Gewünschte Qualifikationen: Must have an above-average degree in relevant fields and experience in simulation methods and Python coding.
- Andere Informationen: Diversity and inclusion are core to our culture; all applications are welcome!
Das voraussichtliche Gehalt liegt zwischen 36000 - 60000 € pro Jahr.
PhD- Virtual Reliability Assessment: New Methods for Leveraging the Simulation Chain
- Full-time
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!
Responsibilities:
- 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.
Minimum Requirements:
- 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
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 further information about the job?
Benjamin Maier (Functional Department)
+49(0711)811-33891
#J-18808-Ljbffr
PhD- Virtual Reliability Assessment: New Methods for Leveraging the Simulation Chain Arbeitgeber: VERA Security, Inc.
Kontaktperson:
VERA Security, Inc. HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: PhD- Virtual Reliability Assessment: New Methods for Leveraging the Simulation Chain
✨Tip Number 1
Make sure to familiarize yourself with the latest advancements in simulation methods and AI/LLM frameworks. This knowledge will not only help you during the interview but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with professionals in the industry through networking events or online platforms like LinkedIn. Building connections can provide you with insights into the company culture at Bosch and potentially give you a referral.
✨Tip Number 3
Prepare to discuss your previous projects related to simulation technology and data-based modeling. Be ready to explain your thought process, challenges faced, and how you overcame them, as this will showcase your problem-solving skills.
✨Tip Number 4
Practice your presentation skills, especially in both German and English. Since the role requires effective communication, being able to present your ideas clearly will set you apart from other candidates.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: PhD- Virtual Reliability Assessment: New Methods for Leveraging the Simulation Chain
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the responsibilities and requirements. Highlight your relevant experience in simulation methods, AI frameworks, and Python programming in your application.
Tailor Your CV: Customize your CV to emphasize your education and experience related to Mechanical Engineering, Applied Maths, or Computational Science. Include specific projects or research that align with the role's focus on reliability assessment and simulation.
Craft a Strong Cover Letter: Write a compelling cover letter that showcases your passion for the field and your proactive attitude. Mention how your skills in data-based modeling and DoE methods make you a great fit for Bosch's innovative environment.
Highlight Language Proficiency: Since the position requires very good knowledge of both German and English, be sure to mention your language skills clearly in your application. If applicable, provide examples of how you've used these languages in a professional or academic setting.
Wie du dich auf ein Vorstellungsgespräch bei VERA Security, Inc. vorbereitest
✨Showcase Your Research Skills
Be prepared to discuss your previous research experiences in detail. Highlight any projects related to simulation methods or lifespan estimation of components, as this aligns closely with the responsibilities of the role.
✨Demonstrate Your Technical Proficiency
Make sure to showcase your knowledge in Python programming and any experience you have with AI/LLM approaches. Be ready to explain how you've implemented these in past projects, as practical examples will strengthen your candidacy.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially in the context of engineering challenges. Think about how you would approach developing DoE models or evaluating uncertainties in results.
✨Communicate Effectively
Since the role involves presenting findings, practice articulating complex ideas clearly and confidently. Being able to communicate your thoughts in both German and English will be a significant advantage.
