PhD Student - Generative Models for Closed-loop Synthesis | PhD – Generative Models for Closed-loop Synthesis
Robert Bosch GmbH
Job Summary
This PhD position at Bosch focuses on cutting-edge research into advanced generative models, particularly diffusion and autoregressive models, to enhance data efficiency for AI training and validation in real-world scenarios. The successful candidate will develop novel deep generative models to serve as data sources, aiming to substitute real-world data collection which is often time-consuming and expensive. This involves designing new methodologies and control mechanisms for efficient data sampling and interaction within a closed-loop system. The role offers the opportunity to collaborate with experts at the Bosch Center for AI, contribute to scientific publications in top-tier venues, and work within an interdisciplinary and international research team, pushing the boundaries of AI development.
Required Skills
Education
Excellent degree in Computer Science or related field with a focus on Computer Vision and Deep Learning
Experience
- Strong background in deep learning and computer vision
- Experience with deep learning frameworks (TensorFlow, PyTorch)
- Strong programming skills, particularly Python
- Knowledge and experience in deep generative modeling and foundation models (beneficial)
- Experience with publication of peer-reviewed research papers (beneficial)
Languages
Additional
- Not specified
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