Thesis Data Analysis for Porosity Prediction in RTMProcesses

Location

Immenstadt im Allgäu | Germany

Job description

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. Join in and feel the difference.

The Robert Bosch GmbH is looking forward to your application!

Job Description

• You will be supporting an ongoing PhD thesis that focuses on embedding sensors into glass fiber-reinforced polymer (GFRP) components.
• Porosity is an important factor for the quality of FRP components.
• Last but not least, you will create Machine Learning Models for the prediction of porosity in Resin Transfer Molding (RTM)-processes from data of embedded acceleration sensors.

Qualifications

• Education: studies in the field of Data Science, Informatics, Mathematics, Physics or comparable
• Experience and Knowledge: in Data Science/Machine Learning and Time Series Analysis, Programming in Python, experience in PyTorch or comparable and Unix systems
• Personality and Working Practice: work independently, solution-oriented, analytical thinking, open to challenges and autodidactic
• Languages: very good German and good English

Additional Information

Start: according to prior agreement
Duration: 6 months

Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.

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?
Markus Münch (Business Department)
+49 8323 20 4896

#LI-DNI

Summary

• Type: Full-time
• Function: Research

Job tags

Salary