PhD Foundation Models and Agentic AI for Industrial Automation

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 Masters 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

Additional Information :

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 6

Need further information about the job
Daniel Ewert (Functional Department)
49 8

Work #LikeABosch starts here: Apply now!

Remote Work :

No

Employment Type :

Full-time