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PhD – Generative Models for Closed-loop Synthesis

Bosch · Software Development · 158,647 employees
On-site Full Time Entry Level years
Posted: October 28, 2026
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Job Description

Company 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!

Job Description

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. 

Qualifications

  • 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

Additional Information

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

Sobre Bosch

The Bosch Group is a leading global supplier of technology and services. It employs roughly 413,000 associates worldwide (as of December 31, 2025). The company generated sales of 91 billion euros in 2025. Its operations are divided into four business sectors: Mobility, Industrial Technology, Consumer Goods, and Energy and Building Technology. With its business activities, the company aims to use t...

Software Development
Setor
158,647+
Funcionários
Gerlingen-Schillerhöhe, Baden-Wuerttemberg
Sede

Interested in this job?

Apply now through the company's official website

Job Information

  • Type Full Time
  • Work Arrangement On-site
  • Experience Entry Level years
  • Location Renningen, BW, Germany
  • Posted 11 days ago

About the Company

Bosch
Software Development

The Bosch Group is a leading global supplier of technology and services. It employs roughly 413,000 associates worldwide (as of December 31, 2025). Th...

158,647 employees Gerlingen-Schillerhöhe, Baden-Wuerttemberg Official Website
View Company Profile

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