PhD - Robust Deep Learning in the Physical World
- Robert-Bosch-Campus 1, 71272 Renningen, Germany
- Legal Entity: Robert Bosch GmbH
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Deep learning (DL) has achieved remarkable results for perceptual tasks within the last decade. However, DL-based perception often lacks sufficient robustness for real-world applications, as exemplified by the existence of adversarial examples and the fragility in face of natural distortions not foreseen during training. Besides, there is growing evidence that DL-based perception works differently than human perception on a fundamental level, e.g. relying overly strong on texture cues and on brittle characteristics of the training data.
- Help shape the future: In this PhD, we want to work on fundamentally new methods for DL, for instance new network architectures, new training procedures, or new regularization schemes.
- Networked communication: The results should be published at the top-tier machine learning venues.
- Personality: Communcative and team player
- Working Practice: Independent, motivated to work in an interdisciplinary and international team
- Experience and Knowledge: With deep learning frameworks (TensorFlow, PyTorch, etc.), basic knowledge of machine learning and deep learning, strong programming skills, in particular Python and strong mathematical background
- Languages: Very good in English (written and spoken)
- Education: Excellent degree (Master) in computer science, mathematics or related fields with excellent marks.
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?
Jan Hendrik Metzen (Functional Department)
+49 711 811 48904