Demonstrate alignment with the core question and clearly articulate your interest in generative modelling, active inference, or understanding adaptive behaviour in neural and/or AI systems.
Highlight relevant technical skills and experience in Python, data analysis, machine learning, or computational neuroscience will strengthen your application—even if not all are required.
Show curiosity about interdisciplinary problems as this project sits at the intersection of neuroscience, AI, and dynamical systems, an openness to multiple perspectives is important.
Emphasise problem-solving and research thinking through prior experience designing experiments, analysing data, or working with models is more valuable than familiarity with specific tools.
Be comfortable with ambiguity as the project explores an open scientific question without a predefined answer—motivation to engage with uncertainty is key.
Communicating clearly and concisely as a strong application will explain your interest and relevant experience in a focused and accessible way.
Interest in neural data or closed-loop systems is a plus and a prior exposure to time-series data, electrophysiology, or interactive systems will be helpful but is not required.