PhD Position - 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 data efficiency in real-world Bosch systems. The successful candidate will explore creative applications of generative models (like Stable Diffusion) as controllable dataset representations for training and validating downstream neural networks. Key responsibilities include developing novel learning algorithms to generate relevant data 'on demand' based on the network's needs, thereby improving training efficiency and ensuring desired invariance. Applicants must hold an excellent degree in Computer Science or a related field with a focus on Deep Learning and Computer Vision, possess strong programming skills (especially Python), and have experience with Deep Learning frameworks (TensorFlow, PyTorch). This role offers the opportunity to collaborate with experts at the Bosch Center for AI and publish findings in high-ranking journals and conferences, making it an attractive opportunity for aspiring AI researchers.