Project Proposal (Master Semester Project):
Neuromorphic devices are now developed to accelerate deep learning at the edge. While a lot of devices are emerging, no comparison between them is available yet, and engineers are required to test several devices to make a choice. This requires time and knowledge of the underlying hardware, which is sometimes impossible in small data engineering teams.
We aimed to develop a benchmarking platform to help designers and engineers to select the best device suitable for their application.
The Edge-AI and Vision group of CSEM is looking to expand the portfolio of applications running on edge devices. In this regard, the group is looking for a student to implement an emotion recognition classifier from public electroencephalographic (EEG) data and deploy it on several edge devices.
- Implementation of State-of-the-Art solutions for emotion classification from EEG signals
- Optimize the algorithm to allow deployment on resource-constrained hardware platforms
- Evaluate the performance of the algorithm for each device
Expected to have experience in:
- Object-oriented programming in Python
- Background in Deep Learning (CNNs, RNNs…) architectures and evaluation
- Experience in Tensorflow/Keras or PyTorch
- Background in signal processing
Interest and experience in:
- Computational Neuroscience
- IoT and embedded devices
- Brain-computer interfaces and electroencephalography
CSEM mission and values
Our mission is the development and transfer of innovative technologies to the Swiss industry and our strength is the excellence of our people who are passionate about technologies and innovation.
- A unique place between research and industry at the cutting edge of new technologies
- An innovative, non-profit, and employee-driven company
- A dynamic, multidisciplinary, and multicultural environment
- being part of a passionate community
- incredible flexibility, attractive working conditions, and great opportunities of development
- benefit from a management style based on trust & feedback and that favors a work-life balance
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity.
We look forward to receiving your complete application file (CV, Cover letter, certificates & diplomas) via our job page.
Preference will be given to professionals applying directly.