PhD in Generative Models for Closed-loop Synthesis

About the role

We are conducting cutting‑edge research on advanced generative models aimed at enhancing data efficiency in Bosch systems. We seek a PhD student passionate about applying diffusion and autoregressive models to simulate real‑world scenarios for AI training and validation.

Key responsibilities

• Develop novel deep generative models (e.g., diffusion models) as data sources to enhance the training and validation of downstream models.
• Collaborate with deep‑learning and computer‑vision experts at the Bosch Center for AI to brainstorm and develop new ideas.
• Aim for publications in top‑tier journals and conferences.

Required profile

• Excellent degree in Computer Science or a related field with a focus on Computer Vision and Deep Learning.
• Strong background in deep learning and computer vision, with experience using TensorFlow, PyTorch, and Python programming.
• Motivation to work in an interdisciplinary, international team; very good English and academic writing skills.

Required skills

• Python programming.
• TensorFlow or PyTorch.
• Deep learning and computer vision.
• Deep generative modeling (diffusion, autoregressive models) – a plus.