We build the first brain-wearable that fits in your ear
Duration: 6 Months from January 2021
Interviews will happen in November
Wisear develops a solution that allows audio manufacturers to transform their true wireless earphones into brain recording devices.
Today we are able to record brain electrical activity – called electroencephalogram or EEG – using electrodes placed on the scalp. The extent of the potential use cases is massive (medical diagnosis, brain performance enhancement, relaxation coaching, etc.). But the size and looks of current devices prevents their usage by the public on a daily basis, as would be necessary to unlock the most promising use cases.
Recent progress in the technology now allows recording EEG signals using electrodes placed in the ear – referred to as “ear-EEG”. It is then possible to include this technology in devices such as true wireless earphones, which will open brain recording to a large audience and let people follow insights and biomarkers based on brain activity on a daily basis.
Wisear builds the first ear-EEG data processing solution for earphones manufacturers, along with accompanying them to turn their earphones into brain recording devices. The first use case covered is the diagnosis and improvement of the user’s attention. We are convinced that in the near future, ear-EEG will be a key technology for early diagnosis and treatment monitoring of brain pathologies (e.g. epilepsy, ADHD, depression, Parkinson’s, etc.)
You will join the team to design and implement signal processing algorithms, in order to create or improve the different solutions provided by Wisear for measuring attention and other brain states. Your main tasks will include :
- Review scientific literature concerning :
- Reference tests used in cognitive psychology studies to measure attention
- Attention measurement based on EEG signal
- Techniques for measuring EEG signal from the ear
- Design and run attention tests on subjects, in order to collect labeled data
- Design and implement artificial intelligence algorithms for attention diagnosis based on ear-EEG data
- Collaborate with academic partners
We are looking for a highly motivated engineering student with strong knowledge and skills in the following areas :
- Digital signal processing:
- Spectral analysis (Fourier and wavelets)
- Filtering – application and optimization
- Machine learning:
- Supervised and non-supervised techniques
- Feature extraction and selection techniques
- Outliers removal techniques
- Parameters fine tuning techniques
- Experience in developing signal processing and machine learning algorithms using one of the following languages : Python (preferred), * MATLAB, R
- Conversational level required
Considering that the company is at a rather early stage, each team member is very likely to have a strong impact on the project. We are looking for a teammate who demonstrates autonomy, and shares our genuine curiosity and strong interest for this marvelous topic that is understanding the brain!
To apply for this job email your details to firstname.lastname@example.org