Postdoctoral Fellow, Multimodal Machine Learning

The Postdoctoral Fellow will develop techniques to build a foundation model of human neurotypes by integrating cognitive task performance, conversational text, and biometric data. The role focuses on utilizing self-supervised representation learning to construct a continuous latent manifold of individual differences. This position involves training models with novel multi-modal architectures and designing rigorous evaluations for participant-level data separation and model robustness.