Research Scientist: Hierarchical RL Agents

We are seeking brilliant, unconventional thinkers to join us. In this role, you will not be chasing incremental gains on standard benchmarks. Instead, you will be tasked with developing the foundational principles of Artificial General Intelligence. We believe that understanding the "code of the brain" is the most viable path to building truly intelligent machines, and we are looking for scientists who can bridge the gap between biological intelligence, computational theory, and building at scale.

• Fundamental Research on Hierarchical World Model Learning from Experience: Develop and implement new architectures and learning/inference algorithms for hierarchical RL that supports hierarchical world modeling and hierarchical planning.
• Ethologically constrained learning: Design tasks to evaluate the agent in ethologically constrained environments, and benchmark different agent designs. Design experiments to test hypotheses regarding high-level cognition, causal representations, sensory-motor integration, active inference, and unsupervised learning.