Pabel is an AI research lab building foundation models of functional brain biology. We're building a future where AI helps develop more effective therapies and brings precision medicine to neurology.
Our partners are the NVIDIA Inception Program, Google for Startups, and the Neurology department of LMU Klinikum Großhadern (Prof. Dr. Jan Rémi).
Tasks
- Develop performant, distributed pipelines and algorithms for EEG data processing and analysis
- Perform rigorous quality checks and preprocessing to ensure data integrity
- Experiment with different parameters to optimize EEG data collection and analysis conditions
- Collaborate with computational neuroscientists, ML researchers, and engineers on cutting-edge research projects
Requirements
- Strong programming skills in Python with ability to quickly learn new frameworks
- Solid understanding of algorithms and data structures
- Problem-solving mindset with attention to detail in experimental work
- Enthusiasm for learning about neuroscience and brain-computer interfaces
- Experience with EEG is a plus but not required
Benefits
- Full research autonomy
- No bureaucracy, no review committees
- €20/hour
- Potential for full-time conversion based on performance
As a Research Intern, you will contribute to building the computational infrastructure that powers our breakthrough EEG foundation model research. You'll work at the intersection of neuroscience and machine learning, developing and optimizing pipelines that process massive EEG datasets and implementing cutting-edge deep learning experiments. This role offers hands-on experience with state-of-the-art neural decoding technology while working alongside world-class researchers pushing the boundaries of what's possible in EEG models.
EUR 400-800 per month