PhD Candidate in Human Navigation and Artificial Intelligence

Job summary

This position involves a 3-year PhD scholarship focused on understanding how humans learn and adapt to navigate urban environments through the integration of artificial intelligence and neuroscience. The research will be conducted at a leading technical university in collaboration with an international partner, emphasizing the development of biologically grounded behavioral models for urban mobility.

Qualifications

• A two-year master's degree or equivalent in cognitive science, computational neuroscience, transport modeling, data science, or a related field.
• Strong quantitative and programming skills.
• Experience with Python, R, Julia, MATLAB, or similar tools.
• Knowledge of behavioral modeling, reinforcement learning, or machine learning.
• Interest in experimental design and human-subject studies.
• Excellent written and spoken English.

Responsibilities

• Develop and validate learning-based behavioral models for navigation and route choice.
• Apply computational neuroscience methods to analyze human mobility behavior.
• Conduct immersive virtual reality experiments and naturalistic field studies.
• Integrate behavioral data with neurophysiological markers.
• Translate research insights into practical tools for urban planning.

Skills

• Strong programming and quantitative analysis skills.
• Familiarity with eye-tracking, EEG, and physiological sensing technologies.
• Ability to work independently and collaboratively in an interdisciplinary team.

Education

• Master's degree in a relevant field.

Tools

• Python, R, Julia, MATLAB, eye-tracking technology, EEG equipment, virtual reality systems.