Working Student in Neural Network Training and Hardware-Aware Optimization for AI Systems

Developing innovative technology solutions and bringing them to application - that is our goal at the Fraunhofer Institute for Photonic Microsystems IPMS. With our expertise in the development of photonic microsystems, related technologies including nanoelectronics and wireless communication solutions, we create - in flexible and interdisciplinary teams - technologies for innovative products in a wide range of markets such as automotive, industrial and aerospace.

At the Center for Nanoelectronic Technologies (CNT) of Fraunhofer IPMS, we focus on developing advanced AI systems through the integration of both Convolutional Neural Networks (CNNs) and Spiking Neural Networks (SNNs). This position will involve training and optimizing these neural networks using Python frameworks, including CUDA, Keras, PyTorch, and SNN-specific libraries like SNNtorch. The role will also explore hardware-aware design strategies such as quantization, error resilience, and co-training techniques for optimized performance on neuromorphic hardware.

What you will do

• Develop and train CNN and SNN models using frameworks like Keras, PyTorch, and SNNtorch
• Implement GPU acceleration using CUDA for efficient training of neural networks
• Explore hardware-aware design concepts such as quantization, error injection, and mixed-precision training
• Design co-training methods to improve model resilience to hardware imperfections and failures
• Analyze model performance, including the impact of hardware-aware strategies on efficiency and accuracy
• Collaborate with other researchers to adopt neural network models for hardware-specific optimizations
• Document the research process, experimental results, and best practices for future projects

What you bring to the table

• Studies in the field of electrical engineering, computer science, AI, or a related field
• Strong understanding of neural networks, including both CNNs and SNNs
• Practical experience with Python frameworks for neural network development, such as Keras, PyTorch, and SNNtorch
• Familiarity with GPU acceleration using CUDA
• Optional: Understanding of digital and analog electronic basics
• Experience with hardware-aware techniques, including quantization and resilience strategies, is a plus
• Excellent command of written and spoken English for effective communication in an international team
• Ability to independently familiarize yourself with new technical domains and complex scientific concepts

What you can expect

We offer you an exciting task and valuable insights into the methods and procedures of a modern high-tech research institute. A motivated and dynamic team awaits you in a very well-equipped research and development environment. In addition, we offer you connecting points within the framework of your studies or your career entry, e.g. a topic for your thesis or the beginning of your career at Fraunhofer IPMS. We support you!

The weekly working time is a maximum of 20 hours and is to be coordinated flexibly. The position is initially limited for 1 year. A long-term collaboration is strived. We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Remuneration according to the general works agreement for employing assistant staff.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future. 

Interested? Apply online now. We look forward to getting to know you!

Contact

Mrs. Sabrina Weimert
Human Resources
Phone: +49 351 8823 415
 

Mr. Alptekin Vardar
Specialty Department
Phone: +49 351 2607 3201

Fraunhofer Institute for Photonic Microsystems IPMS

www.ipms.fraunhofer.de 

Requisition Number: 77874