We're building a system that represents domain knowledge as modular probabilistic models — making analysis rigorous and transparent by design. Users can connect these models flexibly into larger structures. The system enforces consistency across them, and propagates uncertainty through every step. Our first applications are in finance and scientific research, with use cases ranging from equity valuation and distress monitoring, to particle physics.
We use category theory to reason about our system end-to-end: from natural language processing and knowledge representation to probabilistic programming and our user interface. We are currently hiring for an Applied Category Theory Researcher to help us research and develop our category theoretic representations of real world phenomena.
PhD (or equivalent research experience) which involved category theory
Programming in some functional or statically typed programming languages, e.g. Rust, OCaml, Clojure, C++, or Haskell
Writing about category theory in accessible ways
Theory building in computer science, applied mathematics or statistics
Familiarity with some of the listed concepts:
(Logical) foundations of computation
Synthetic probability theory
Probabilistic graphical models (including Bayesian networks)
Denotational semantics
String diagrams, monoidal categories, optics, lenses
Follow existing literature and bring up relevant ideas
Formalize the categorical semantics of our probabilistic DSL, feeding back theoretical insights for the benefit of the implementation
Develop new models for real world phenomena along our framework, for example, relationships, probabilistic models, dynamical systems, and natural language
Present results of your work in a way accessible to experts in other fields
We've found that our successful team members share some key characteristics, and as we've grown our team, these are the qualities we've learned to seek out. We take pride in our strong, collaborative culture, and these core attributes not only reflect our shared values, but can help you evaluate how well you might fit into our team:
A builder at heart: You’re passionate about building things, solving complex problems, and approaching challenges with an entrepreneurial spirit and humility. Your sharp sense of prioritisation gives you a laser focus on delivering results that uplift the entire team, moving us closer to our goal.
Results-driven: You thrive when taking full ownership of tasks, seeing them through from start to finish, and taking accountability for the results. You’re proactive, resourceful, and avoid over-complication - anticipating problems, even in complex, uncertain environments.
Growth mindset: You are intellectually curious, have a critical mind, and seek opportunities to stretch your abilities. You explore the state-of-the-art, you dig deep to truly understand a problem, and question assumptions.
A strong collaborator: You naturally communicate with clarity and purpose, ensuring your ideas and updates are easily understood. You work efficiently, embracing an iterative approach that allows for frequent progress and course correction. You’re open to direct feedback, adapting quickly and using it to improve both your work, and the performance of those around you.
Approaching problems and tasks like a project manager:
You can take a given goal and break it down into smaller parts.
You can solve problems systematically, by yourself as well as collaboratively with others.
You involve others in effective problem-solving sessions because you value getting to the best solution over being right.
You document processes well to ensure others can jump in to collaborate effectively.
On our website you can find more about our team and work culture, as well as example tasks that share some insight into the type of things team members are working on.
What we do: https://planting.space/
Ways of work: https://planting.space/org/
Team culture and example tasks: https://planting.space/joinus/
Our team works fully remotely, and mostly within the CET timezone.