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 master thesis you will apply and adapt state-of-the-art sequence models from recent publications in the field of machine learning, in the context of virtual sensors for the smart and safe e-bike of the future.You will train and compare models to assess their suitability and performance, while experimenting with the training scheme.Ideally a demonstrator of the final approach will be realized to validate the functionality.

QualificationsEducation: master studies in the field of Computer Science, Artificial Intelligence, Mechatronics, Electrical Engineering, Cybernetics or comparable with good gratesExperience and Knowledge: in the field of machine learning; good Python programming skills; practical experience with ML libraries like PyTorch or TensorFlow and neural network training; ideally first experiences with sequence models (LSTMs, GRUs, transformers, ...); knowledge in the fields of state estimation and vehicle dynamics are an advantagePersonality and Working Practice: motivated to try out and learn new things with an independent and systematic approach to the taskLanguages: fluent in English or German

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?
Alessandro Moia (Functional Department)
+49 711 811 43672
Silas Klug (Functional Department)
+49 711 811 8344

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