About the job
We are conducting cutting-edge research on advanced generative models aimed at enhancing data efficiency in Bosch systems. We are seeking a PhD student who is passionate about exploring innovative applications of generative models (such as diffusion and autoregressive models) to simulate real-world scenarios for AI training and validation.
Responsibilities
Develop novel deep generative models (e.g., diffusion models) as data sources to enhance the training and validation of downstream models.
Collaborate with experts in deep learning and computer vision at the Bosch Center for AI to brainstorm and develop new ideas.
Aim for publications in top-tier journals and conferences.
Qualifications
Minimum
Education: excellent degree in Computer Science, or related field with focus on Computer Vision and Deep Learning
Experience and Knowledge: strong background in deep learning and computer vision, experience with deep learning frameworks (TensorFlow, PyTorch, etc.), strong programming skills, in particular Python, knowledge and experience in deep generative modeling as well as foundation models are a plus, experience with publication of peer-reviewed research papers is beneficial
Enthusiasm: motivation to work in an interdisciplinary and international team
Languages: very good English skills and academic writing skills
Preferred
knowledge and experience in deep generative modeling as well as foundation models are a plus
experience with publication of peer-reviewed research papers is beneficial