Student project: Sensor fusion on Embedded DNN accelerator

What you will do

This project targets hardware-efficient embedded deep-learning solutions for sensor fusion applications to be used in various practical scenarios. Here are the steps toward finalizing the project:

• Literature review on the application, available neural networks to address the problem and the target embedded deep learning accelerator.
• Selection and optimization of the algorithm for the target hardware.
• Implementation, measurements, and benchmarking.
• Documentation and thesis writing if required.

Similar research example: Moosmann, Julian, et al. "TinyissimoYOLO: A Quantized, Low-Memory Footprint, TinyML Object Detection Network for Low Power Microcontrollers." arXiv preprint arXiv:2306.00001 (2023).

What we do for you

Imec provides the equipment, expert supervision, monthly stipend and office space to the student. Hardware Efficient AI team in imec has a unique research and development culture which prepares students to experience practical research activities.  

Who you are

• MSc student in Electrical Engineering or Computer Science.
• Knowledge and interest in deep learning.
• Available for a period of 6 months.
• Experience with programming low-level hardware (C/C++) and scripting languages such as Python.
• Structured way of reporting, both orally and in writing.
• Understanding of Neuromorphic design is a plus.
• Motivated student eager to work independently and expand knowledge in the field.
• Entitled to do an internship in the Netherlands. This means that you are either an EU/EEA citizen, or a non-EU/EEA citizen who is studying at a Dutch university and need to do an internship as part of your studies. 

Interested

Does this project sound like an interesting next step in your career at imec? Don’t hesitate to submit your application by clicking on ‘APPLY NOW’.
Should you have more questions about the recruitment process? Martijn Kohl of the Talent Acquisition Team will be happy to assist you.