/Student project: Neuromorphic spiking neural network digital design for decoding neural activities

Student project: Neuromorphic spiking neural network digital design for decoding neural activities

Research & development - Eindhoven | More than two weeks ago

The scope of this research is to design a spiking neural network hardware that is capable of decoding the neural activity of populations of neurons, for future brain-computer interface applications.

Student project: Neuromorphic spiking neural network digital design for decoding neural activities

Neuromorphic spiking neural network digital design for decoding neural activities.

What you will do

A Brain Computer Interface (BCI) allows direct communication between the brain and a computer by interpreting electrical signals generated by the brain, enabling users to interact with technology using only their thoughts. Neural decoding is the process of analysing and interpreting patterns of electrical signals generated by groups of neurons to determine information about a person's behaviour, cognition, or mental state. One way to decode such neural patterns is to use a neural network model that mimics the brain behaviour itself, i.e., Spiking Neural Networks (SNN). Neuromorphic SNNs are typically more energy-efficient and lower latency, and well-suited for real-time processing than traditional neural networks.  

This MSc proposal focuses on the design of a Spiking Neural Network for neural decoding, with the focus on its hardware implementation aspects. The tasks to be performed are:

  • Literature study on the state-of-the-art of the SNN.
  • Architecture study and modeling of the SNN.
  • Digital design of the SNN.
  • Simulation with neural dataset.
  • Hardware validation with e.g., FPGA and lab-test

What we do for you

As one of the world's best research institutes, we can offer you a fantastic opportunity to boost your career. In this internship project, you will be working on an innovative research project, under the supervision of world-renown researchers from diverse backgrounds and in a dynamic and multicultural environment.

Who you are

  • Electronics Engineering Master student with interest in biomedical systems and AI related topics.
  • Good analytical and modeling skills.
  • Knowledge of Neural Networks and Machine Learning.
  • Experience with mathematical tools and programming languages (Python, MATLAB).
  • Experience with HDL (Verilog, VHDL) and digital design tools (Vivado).
  • Experience with FPGA programming and testing is a plus.
  • Available for a period of 9-12 months.
  • Entitled to do an internship in the Netherlands. 
  • Motivated and eager to work independently and expand knowledge.
  • Good written and verbal English skills.

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’.
Got some questions about the recruitment process? Martijn Kohl of the Talent Acquisition Team will be happy to assist you.

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