Applied Category Theory Researcher
Role overview
About the Company Planting is building a system that represents domain knowledge as modular probabilistic models, making analysis rigorous and transparent. The system uses category theory to reason about everything from natural language processing to probabilistic programming, with applications in finance and scientific research. Responsibilities Follow existing literature and bring up relevant ideas Formalize the categorical semantics of the probabilistic DSL Feed back theoretical insights for the benefit of the implementation Develop new models for real world phenomena including relationships, probabilistic models, dynamical systems, and natural language Present results of work in a way accessible to experts in other fields Requirements PhD or equivalent research experience involving category theory Programming experience in functional or statically typed languages (e.g., Rust, OCaml, Clojure, C++, or Haskell) Experience writing about category theory in accessible ways Experience in theory building in computer science, applied mathematics, or statistics Familiarity with concepts such as synthetic probability theory, probabilistic graphical models, denotational semantics, string diagrams, monoidal categories, optics, or lenses
