PhD – Generative Models for Closed-loop Synthesis

Renningen, BW, de on site Until 9/13/2026 H-1B sponsor history First posted July 15, 2026 Last posted July 15, 2026
Job description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: We grow together, we enjoy our work, and we inspire each other. Welcome to Bosch.

The Robert Bosch GmbH is looking forward to your application!

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. 

The development of AI models is often an iterative process that requires increasingly large datasets to address long-tail cases that are not represented in existing data. However, collecting data from the real world can be time-consuming and expensive, hindering the automation of the data loop. The objective of this thesis is to create new methodologies that enable generative models to substitute for the real-world, facilitating closed-loop interactions. This may involve designing novel control mechanisms to efficiently sample the required data and respond to interactions.

As a member of our team, you will: 

  • 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. 
  • 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

https://www.bosch-ai.com
www.bosch.com/research

Please submit all relevant documents (incl. curriculum vitae, certificates).

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need support during your application?

Sarah Schneck (Human Resources)
+49 711 811-43338

Need further information about the job?
Jiayi Wang (Functional Department)
+49 711 811 44429
Julia Vinogradska (Functional Department)
+49 711 811 27767

About this role

Summary

Researching generative models to enhance data efficiency and simulate scenarios for AI validation.

Job title

PhD – Generative Models for Closed-loop Synthesis

Experience level

PhD student

Industry

software

Location requirements

Renningen, BW, Germany, no remote work allowed.

Salary

Not specified

Visa sponsorship

H-1B sponsor history

Management role

No

Skills & keywords

Required skills

deep learningcomputer visionPythongenerative modelsTensorFlowPyTorch

Preferred skills

foundation modelspeer-reviewed publications

Specializations

deep learningcomputer visiongenerative modelsPyTorchTensorFlow
Locations

Structured locations inferred from the posting.

71 Renningen, Germany

On-site City