28 Wissenschaft / Forschung Jobs in Baden-Württemberg

Job Description

Industrial automation is at a turning point. Foundation models offer unprecedented generalization and adaptability — yet deploying them in real production environments means addressing strict constraints: microsecond-level latencies, deterministic behavior, functional safety certifications, and legacy infrastructures that cannot simply be replaced.

• As a PhD candidate, your tasks will include investigating how foundation models can be effectively applied in industrial reality. To this end, you will develop innovative methods for adaptation, validation, and deployment.
• You will bring these models into manufacturing, the process industry, and cyber-physical systems, always treating latency, determinism, and safety as non-negotiable factors.
• In addition, you will address key questions such as how foundation models can deliver bounded, predictable performance without compromising their capabilities.
• You will develop solutions to ensure compatibility between foundation models and established industrial safety and automation standards (e.g., IEC 61131, IEC 61508).
• Last but not least, you will enhance brownfield automation platforms with the capabilities of foundation models, thereby unlocking new opportunities for industry.

Qualifications

• Education: completed Master’s degree in Computer Science, Electrical Engineering, Industrial Automation, Robotics, Mechatronics, or a comparable field
• Experience and know-how: strong theoretical and practical background in machine learning and deep learning; solid understanding of industrial automation concepts, control systems, as well as real-time or embedded environments; proficient programming skills in Python and C++; familiarity with functional safety standards (IEC 61508, ISO 13849) as well as formal verification or validation methods; proven experience in deploying and optimizing AI models on edge devices, embedded hardware, or resource-constrained platforms; knowledge of model optimization techniques such as quantization, pruning, knowledge distillation, or accelerated inference; practical experience with PLC environments, industrial communication protocols (OPC UA, PROFINET, EtherCAT), or industrial real-time platforms is desirable
• Personality and working style: strong interest in applying foundation models in industrial or cyber-physical systems and the ability to approach complex research questions in a structured and methodical way
• Languages: fluent English (written and spoken) and good German skills

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

The final PhD topic is subject to your university.

Please submit all relevant documents (CV, certificates, and links to GitHub or kaggle account).

Start: according to prior agreement

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?
Celina Dannecker (Human Resources)
+49 711 811 21346

Need further information about the job?
Daniel Ewert (Functional Department)
+49 711 811 11758

Work #LikeABosch starts here: Apply now!