The industrial doctorate at Infineon: Pursue a doctoral degree at a university and gain professional experience simultaneously - an ideal start for your career. Advance your research with us and profit from our vast network of doctoral candidates and the expertise of a university. Mentorship is handled by both professors and dedicated Infineon employees. This thesis explores the deployment of generative AI models, including transformers, convolutional networks, and other architectures, across various modalities—such as natural language, vision, and audio—on resource-constrained embedded systems like microcontrollers. It addresses challenges of limited memory, computational capacity, energy efficiency, and low-latency requirements. The research investigates state-of-the-art techniques such as model compression, architecture optimization, and cross-modal co-design, while also proposing custom microcontroller enhancements, such as specialized accelerators and approximate computing techniques, to support diverse AI workloads. Through prototype implementations and real-world validation, this work aims to enable energy-efficient, scalable generative AI across a range of modalities, supporting the next generation of IoT and edge computing systems. The research is carried out in cooperation with the University of Otto-von-Guericke Magdeburg and under the supervision of Prof. Dr. Fabian Lurz.Job Description
The tasks within the thesis will consist of:
1. Research on GenAI literature and selection of tools and pipelines for embedded deployment
2. Application of selected methods on available sensor data ( microphone +radar + camera, etc.)
3. Consolidation of selection of (embodied multi-modal) LLM model and processing pipeline
4. Optimization and deployment models to embedded compute platforms (Cortex A,M55/U55, M85/U65)
5. Propose accelerator architecture for selected GenAI architecture(s)
6. Implementation of a demonstrator / POC on FPGA platform
The learnings out of the thesis will lead to:
7. Optimized Deployment Strategies: Frameworks for deploying generative AI models across multiple modalities (language, vision, and audio) on resource-constrained systems
8. Energy-Efficient AI Solutions: Techniques to improve the energy efficiency and real-time performance of embedded AI workloads
9. Hardware-Software Co-Design: Insights into extending microcontroller architectures with lightweight accelerators or memory optimizations for generative AI
10. Advanced Model Optimization: Enhanced methods for model compression, quantization, and sparsity tailored for ultra-constrained devices
11. Proven Prototypes: Real-world implementations demonstrating generative AI applications like voice processing, anomaly detection, and IoT analytics
12. Future Research Pathways: A foundation for exploring neuromorphic computing, hybrid edge-cloud systems, and scalable AI for edge applications
Your Profile
A doctoral student is a research enthusiast,
…whose interests are scientific research combined with the passion for Infineon’s innovative products and applications.
…who enjoys working in an industrial environment in combination with an Infineon partner university.
…who appreciates open communication and the contribution of an international environment.
…and is thus an excellent candidate for a further academic or industrial career after completion of their thesis.
As the ideal candidate you:
13. Are eligible for full-time PhD studies and have a master’s degree in Electrical Engineering, Computer Science, or a closely related field
14. Already have some experience in deploying ML models on embedded hardware, such as TensorFlow Lite for - Microcontrollers or Apache TVM
15. Have strong proficiency in machine learning techniques and frameworks, including TensorFlow, PyTorch, and Keras
16. Have in-depth understanding of microcontroller architectures and machine learning accelerators
17. Have solid expertise in digital circuit design and familiarity with common EDA tools for FPGA development, such as Vivado
18. Are you enthusiastic about scientific work
19. Question the status quo and like to break new ground
20. Have good oral and written communication skills in English
Benefits
21. Coaching, mentoring networking possibilities
22. Wide range of training offers & planning of career development
23. International assignments
24. Different career paths: Project Management, Technical Ladder, Management & Individual Contributor
25. Flexible working conditions
26. Home office options
27. Part-time work possible (also during parental leave)
28. Sabbatical
29. On-site creche and kindergarden with 220 spots, open until 5:30pm
30. Holiday child care
31. On-site social counselling and works doctor
32. Health promotion programs
33. On-site gym, jogging paths, beachvolleyball, tennis & soccer court
34. On-site canteen
35. Private insurance offers
36. Wage payment in case of sick leave
37. Corporate pension benefits
38. Flexible transition into retirement
39. Performance bonus
40. Reduced price for public transport and very own S-Bahn station
41. Access for wheelchairs
42. Possibility to work remotely from abroad (EU)