PhD Position: Investigating Neurotechnological Systems with Machine Learning Techniques
4 weken geleden
We are seeking a highly motivated PhD candidate to join our research team at Radboud University. The successful candidate will have the opportunity to work on a cutting-edge project investigating the role of user feedback and introspection mechanisms in neurotechnological systems.
Project OverviewThe project aims to develop and evaluate closed-loop brain-computer interface protocols using machine learning techniques. The candidate will design and implement experimental protocols in Python to study the introspection ability of BCI users and the role of feedback. The research will involve conducting non-invasive EEG studies with healthy participants and patients, and cooperating with our clinical partners.
Responsibilities- Design and implement experimental protocols in Python
- Conduct non-invasive EEG studies with healthy participants and patients
- Cooperate with clinical partners
- Train machine learning models to analyze data
- Participate in the scientific dissemination of results
- Master's degree in Artificial Intelligence, Computer Science, Cognitive Neuroscience, or a related discipline
- Strong interest in neurotechnological systems and machine learning
- Excellent programming skills in Python
- Experience with neuroscientific data analysis
- Excellent written and spoken English language skills
- Temporary employment contract for 1.5 years, with the possibility of extension
- Starting salary of €2,770 gross per month, increasing to €3,539 in the fourth year
- 8% holiday allowance and 8.3% end-of-year bonus
- Access to our Dual Career and Family Support Service
We are an equal opportunities employer and welcome applications from candidates with diverse backgrounds and perspectives. If you are passionate about research and have a strong interest in neurotechnological systems, we encourage you to apply for this exciting opportunity.
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