Fluency in 2 or more of { category theory, Haskell (Idris/Agda/...), deep learning } required. Check out our open positions at the provided link for more details.
We're trying to apply the insights of category theory, dependent type theory, and functional programming to deep learning. How do we best equip neural nets with strong inductive biases from these fields to help them reason in a structured way?