Thesis Using Geometrical Deep Learning for Simulation

• During your thesis you will familiarize yourself with the software landscape for simulation at Bosch Power Tools.
• You will conduct a literature review on the topic of Geometrical Deep Learning from an application-oriented perspective.
• Furthermore you will work with and evaluate a commercially available tool.
• Your job includes the integration and implementation of existing simulation models and data. You will train AI models with already existing simulation results and evaluate the quality and plausibility of the obtained AI model results.
• Finally you will derive recommendations for the use of these models in the context of Power Tool simulations.

Qualifications :

• Education: studies in the field of Mechanical Engineering Mechatronics Aerospace Engineering Computational Engineering or comparable with a focus on mechanics and dynamic simulation
• Experience and Knowledge: confident use of MS Office initial knowledge of FEM simulations (ideally Abaqus and HyperWorks); fundamentals of Data Science
• Personality and Working Practice: you excel at proactively and responsibly driving tasks forward leveraging your strong analytical and communication skills to work effectively both independently and as a collaborative team member
• Work Routine: your on-site presence is required
• Languages: fluent in English and German

Additional Information :

Start: according to prior agreement
Duration: 4 - 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.

You are almost finished with your Bachelors degree and would like to gain some practical experience before embarking on your next academic adventure with a Masters degree Then you fit in perfectly well with our PreMaster Program! Take a look at our vacancies here.

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
Udo Hartel (Functional Department)
49 711 

Work #LikeABosch starts here: Apply now!

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Remote Work :

No

Employment Type :

Full-time