Master Thesis in Evaluation and Implementation of Machine Learning Methods for Driver Assistance and Autonomous Driving
28.03.2024
Bosch-Gruppe
Abstatt
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Master Thesis in Evaluation and Implementation of Machine Learning Methods for Driver Assistance and Autonomous Driving
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Master Thesis in Evaluation and Implementation of Machine Learning Methods for Driver Assistance and Autonomous Driving
Abstatt
Aktualität: 28.03.2024
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28.03.2024, Bosch-Gruppe
Abstatt
Master Thesis in Evaluation and Implementation of Machine Learning Methods for Driver Assistance and Autonomous Driving
During your master thesis, you will contribute to scientific research in the field of autonomous driving and advanced driver assistance systems.
You will work with data from various sources in the automotive domain, i.e. extract, pre-process and enrich data, develop models and visualise results.
Furthermore, you will conceptualize and setup processing pipelines and tools.
In addition, you will get the chance to work with experienced software developers and be part of an agile team. Furthermore, you will have the chance to work mobile partially.
Finally, you will contribute to something big, such as exploring the possibilities of synthetic data or anonymisation, and the exact tasks will depend on your previous experience.
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Master Thesis in Evaluation and Implementation of Machine Learning Methods for Driver Assistance and Autonomous Driving
Job ID REF226335R
LocationAbstatt , Germany
Fields of workInformation Technology
Join asNot Applicable
Job typeFull-time
Start DateAccording to arrangement
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Welcome to Bosch
Your tasks
Your profile
Education: Master studies in the field of Science, Technology, Engineering, Mathematics or comparable with good grades
Experience and Knowledge: programming experience, especially in Python, knowledge in AI / Machine Learning, ideal knowledge in a relevant data analytics project, i.e. data collection, preparation, processing, modeling, analysis and visualization, experience in PyTorch/TensorFlow and neural networks as well as synthetic environmental generation is beneficial
Personality and Working Practice: motived, self-organized, goal-oriented and team player
Work Routine: partially mobile working within Germany
Languages: fluent in German and English
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