PhD Student - Efficient Neural Representation of Datasets | PhD - Effiziente Neuronale Repräsentation von Datensätzen

Job Summary

This PhD position at Bosch focuses on cutting-edge research in Deep Generative Models to enhance the data efficiency of real-world Bosch systems. The successful candidate will explore innovative applications of generative models, such as Stable Diffusion, for controllable dataset representation crucial for training and validating neural networks. The role involves developing novel learning algorithms to generate relevant data "on demand" based on network needs, improving training efficiency, and ensuring desired invariance through targeted example creation. You will work within an interdisciplinary and international team, contributing to the advancement of Deep Learning and Computer Vision, with opportunities to publish research in top-tier journals and conferences.