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 DescriptionDuring your internship you will work on the further development of an in-house software tool for physical modeling in the context of microfluidics and on the development of a Physics-Informed Neural Networks (PINN) model in PyTorch for simulating microfluidics.You will train and evaluate the PINN model using experimental and numerical data and integrate the trained model into the existing software environment.Furthermore, you will optimize the PINN model's performance regarding computation time, memory requirements and accuracy.Finally, you will collaborate within the development team and participate in regular meetings.

QualificationsEducation: Master studies in the field of Mechanical, Computational, Software Engineering or comparableExperience and Knowledge: very good in programming and machine learning techniques in Python (preferably with PyTorch); good knowledge in code optimization and test-driven software development; solid understanding of basic physics and mathPersonality and Working Practice: you effectively analyze complex problems, work independently to find solutions, collaborate well with others, and communicate clearlyEnthusiasm: strong interest in the field of industrial researchLanguages: fluent in German or English

Additional Information

Start: according to prior agreement
Duration: 6 months

Requirement for this internship is the enrollment at university. Please attach your CV, transcript of records, enrollment certificate, 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?
Alexander Eifert (Functional Department)
+49 711 811 15866
Christian Kuntz (Functional Department)
+49 711 811 6681

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