PhD - AI/ML based credible simulation model of power module for hybrid and

7 Feb 2024
Job Information

Organisation/Company

Bosch

Research Field

Computer science

Researcher Profile

Recognised Researcher (R2)

Country

Germany

Application Deadline

7 Mar 2024 - 00:00 (UTC)

Type of Contract

To be defined

Job Status

Full-time

Hours Per Week

To be defined

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Company Description

Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.

The Robert Bosch GmbH is looking forward to your application!

Job Description

In this scientific work we want to develop a compact digital twin for non-linear and temperature dependent thermo-mechanical behavior. Currently only machine learning models can capture this complex behavior. If you are passionate about technology that is beyond state of the art, strengthen our team. Your task will be:

• Conduct literature research regarding credible simulation approach.
• Development of compact digital twin based on machine learning for uncertainty quantification and robustness analysis of molded power module for coupled thermal and thermo-mechanical loading conditions.
• Development of test structure with piezoresistive stress sensor for validation of the compact digital twin.
• Presentation of work internally within Bosch and during international conferences.
• Cooperation within the framework of publicly funded project with external partners (research and industry leaders).

Qualifications

• Education: Completed university degree (master/diploma) in Computational Engineering, Computational Mechanics, Information Technology, Electrical. Mechanical, or Aeronautical Engineering, Physics, Mathematics or a comparable course of study
• Personality & Working Practice: self-motivated, responsible, innovative, and team-oriented
• Experience and Knowledge: Solid experience in programming/scripting, preferably in Python. Experience with data science / machine-learning. Experience with simulation methods such as FEM, CFD, MOR or design of experiment desirable.
• Languages: fluent in English, German is a plus but not mandatory

Additional Information

The final Phd topic is subject to your university. Start: month year / according to prior agreement

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?
Michelle Kurz (Human Resources)
+49 7121 35-33122

Need further information about the job?
Jakub Przemyslaw Gromala (Functional Department)
+49 162 8514983

Requirements
Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

Bosch

Country

Germany

Geofield

Where to apply

Website

https://illbeback.ai/job/phd-ai-ml-based-credible-simulation-model-of-power-mod…

STATUS: EXPIRED