PhD – Data Efficient Deep Learning

  • Robert-Bosch-Campus 1, 71272 Renningen, Germany
  • Part-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

  • Create something new: You develop and implement novel Deep Learning algorithms. Furthermore, you evaluate these developed algorithms on open datasets and on multi-modal Bosch datasets from application areas such as autonomous driving, robotics, and Internet of Things.
  • Help shape the future: You carry out research on generative models such as Generative Adversarial Networks, with the focus on relaxing the requirement of deep learning for large amounts of labeled data.
  • Observe, and think ahead: You take part in technical discussions and creation of new ideas within the Deep Learning research team at the Bosch Center for Artificial Intelligence.
  • Experience cooperation: You collaborate with Machine Learning and Computer Vision experts.
  • Networked communication: You publish in top-tier journals and conferences.


  • Education: Master of Science in computer science, mathematics, or related fields with excellent grades
  • Personality: Highly self-motivated and strong team player
  • Working Practice: Excellent communication skills and analytical thinking
  • Experience and Knowledge: Basic knowledge of machine learning and deep learning, experience with deep learning frameworks (TensorFlow, PyTorch, etc.), prior experience with generative modelling is a plus
  • Qualifications: Strong programming skills, in particular Python
  • Enthusiasm: Motivation to work in an interdisciplinary and international team
  • Languages: Very good English skills and academic writing skills

Additional Information

The final PhD topic is subject to your university.. Duration: 3 years

Please submit all relevant documents (incl. curriculum vitae, certificates).   

Need support during your application?
Kevin Heiner (Human Resources)
+49 711 811-12223

Need further information about the job?
Michael Pfeiffer (Functional Department)
+49 711 811-18195

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