Data Representation Innovator

We are seeking a highly motivated PhD student to join our team at the Robert Bosch GmbH, a leading technology and services company. The successful candidate will have the opportunity to conduct research on state-of-the-art deep generative models for efficient neural representation of datasets.

The project aims to develop new learning algorithms for generating relevant data "on demand" in response to the needs of downstream networks. This involves improving training efficiency by synthesizing the most relevant data and enforcing desired invariance by creating examples. As part of this project, you will develop novel approaches to adapt deep generative models as data sources to better train and validate downstream models.

Key responsibilities:

• Developing and implementing novel deep generative models for efficient neural representation
• Adapting and integrating these models with downstream tasks to improve training efficiency and robustness
• Collaborating with our team of experts in deep learning and computer vision to advance the state-of-the-art in data-efficient neural representation

Qualifications:

• Master's or Bachelor's degree in Computer Science, related field, or equivalent experience
• Strong background in deep learning, computer vision, and programming skills (Python)
• Experience with deep learning frameworks (TensorFlow, PyTorch, etc.) is beneficial
• Publishing experience in top-tier journals and conferences is a plus

We offer a competitive salary, ranging from €55,000 to €65,000 per year, depending on qualifications and experience. Benefits include remote work options, flexible working hours, and a dynamic work environment. Join us in shaping the future of AI and contribute to cutting-edge research projects at the Robert Bosch GmbH.

Please submit your application, including your CV, certificates, and any additional relevant documents. We look forward to reviewing your application.