PhD – Safe and Efficient Model-Based Reinforcement Learning

  • Robert-Bosch-Campus 1, 71272 Renningen, 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

At Bosch, we have a long and rich engineering history, large amounts of domain expertise and understanding of complex systems. At the same time, we believe that RL is the most promising field in AI and will revolutionize the way we design controllers for real-world systems. However, recent successes in RL on simulated tasks do not directly transfer to real-world systems, that are often safety critical and constrained in the amount of data that can be collected.

To make RL applicable to our real-world systems requires a profound theoretical understanding of the employed methods to guarantee safety of operation while at the same time ensure data efficiency by building on accurate models that incorporate uncertainty as well as existing domain knowledge. This approach opens many interesting research directions in topics related to approximate inference, novel algorithmic contributions, and theoretical analysis.

At the Bosch Center for Artificial Intelligence, we are looking for a motivated PhD student to tackle these interesting problems together with us. During your PhD you will work closely with the active research team at the Bosch Center for Artificial Intelligence and publish results at top tier machine learning conferences. The PhD is focused only on research. However, by working with the team your research results can have direct real-world impact inside Bosch.

  • Take responsibility for the original research by developing, analyzing and evaluating novel model-based reinforcement learning algorithms.
  • Moreover, you will publish in top-tier journals & conferences and supervise our master students.
  • Be part of the existing reinforcement learning and optimization research team and collaborate with machine learning experts at the Bosch Center for Artificial Intelligence.

Qualifications

  • Education: Excellent master degree in machine learning, mathematics, statistics, computer science or related fields
  • Personality and Working Practice: Good communication skills to enable fruitful collaborations with our interdisciplinary team
  • Experience and Knowledge: Proven programming skills, preferably in Python, experience in (deep) reinforcement learning and/or approximate inference is a plus
  • Languages: Good in English (written and spoken)

Additional Information

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

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

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

Need further information about the job?
Felix Berkenkamp (Functional Department)
+49 711 811 44569

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