Doctoral Candidate in Computational Neuroscience | Doctoral Candidate in Computational Neuroscience (m/d/w)

Friedrich-Alexander-Universität Erlangen-Nürnberg

Erlangen, Bayern, Deutschland
Published Jul 18, 2025
Full-time
No information

Job Summary

This fully funded PhD position at FAU Erlangen-Nuremberg focuses on developing AI-driven methods for digital phenotyping using ubiquitous sensor data. The successful candidate will track behavioral and physiological changes, integrating these insights with neuroimaging-informed computational models to optimize neurostimulation strategies. The goal is to personalize therapy for neurological and psychiatric disorders, enabling responsive and adaptive treatment. This role is ideal for a highly motivated individual with a strong background in computer science or biomedical engineering, eager to contribute to cutting-edge research in computational neuroscience and AI for health applications.

Required Skills

Education

Master's degree in Computer Science, Biomedical Engineering, Electrical Engineering, or a related field

Experience

  • Experience with machine learning and AI, ideally in health or behavioral domains
  • Familiarity with ubiquitous/wearable sensor data (e.g., physiological monitoring, smartphone usage)
  • Background in computational modeling of neural systems (e.g., NEURON, The Virtual Brain, Sim4Life) is a strong plus

Languages

English (Basic)

Additional

  • Full-time position (TV-L E13, 100%)