Thesis Deep learning-based algorithm for classifying the driver's drowsiness level

  • Robert-Bosch-Allee 1, 74232 Abstatt, Germany
  • Full-time
  • Legal Entity: Robert Bosch GmbH

Company Description

Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology – with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.

The Robert Bosch GmbH is looking forward to your application!

Job Description

We’re a data science and engineering team that builds and leverages state-of-the-art machine learning systems for developing autonomous driving.
Ideal candidates will use their passion for deep learning to provide insights to the problem of drowsiness detection.
Your work will focus on the development of a deep learning-based algorithm for classifying the driver's drowsiness level.

  • Take responsibility: You identify relevant image segments for the classification task.
  • Create something new: Furthermore you implement and test effective network architectures.
  • Structured evaluation: Last but not least you document the methods used and the results obtained.

Qualifications

  • Education: Master studies in the field of computer science, math or a similar field of specialization
  • Character and Working practice: A creative and logical thinker
  • Experience: In using deep learning frameworks (e.g. Tensorflow, PyTorch, etc.)
  • Knowledge: Skilled in the Python programming language and knowledgeable in the field of deep learning
  • Languages: Good in German and English

Additional Information

Start: January 2020 or according to prior agreement
Duration: 6 months

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

Need further information about the job?
Jihad Miramo (Business Department)
+49 152 08513242

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