We're building a system that represents domain knowledge as modular probabilistic models — making analysis rigorous and transparent. Users can connect these models flexibly into larger structures. The system enforces consistency across them, and propagates uncertainty through each step. Our first applications are in finance and scientific research, with use cases ranging from equity valuation and distress monitoring, to particle physics.
We are looking for full-time researchers to contribute to the development and analysis of our learning algorithms. You will work on interesting theoretical problems with immediate applicability to implementation of our system.
Our team works fully remotely, and mostly within the CET timezone.
Useful experience
Development of mathematical analysis methods, for example: optimal transport, information geometry, continuous optimization methods
Analysis of probabilistic graphical models, including factor graphs
Implementation of tractable density estimators (normalising flows, autoregressive density models, probabilistic circuits)
Translation between equational reasoning and code implementation
Mathematics, Computer Science, or Statistics advanced degree (with PhD or equivalent research experience)
Responsibilities
Develop numerical-analytical models of learning in our system
Connect our research to existing literature
Prove properties of algorithms and design experiments to validate results empirically
Leverage the expertise of other team members effectively
Write clean and well documented code
Help other team members to deliver on their goals
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/
Skills Required
- Development of mathematical analysis methods
- Analysis of probabilistic graphical models
- Implementation of tractable density estimators
- Translation between equational reasoning and code implementation
- Advanced degree in Mathematics, Computer Science, or Statistics (PhD or equivalent)
What We Do
We are a research & development startup building a system which accurately represents knowledge and uncertainty, to enable the discovery of insights and transparent problem solving. Currently we’re focussed on sustainably growing our team in the areas of software development, research, operations and business development. Check out our job page for our full list of opportunities and the skill sets we’re searching for: https://planting.space/joinus/ What matters to us are outcomes, not when and from where our team members work, so positions are remote and not bound to exact work hours. We automate as much as we can, so that we can focus on problems that require creativity, analytical thinking and problem-solving. We regularly meet in nice places to work and have fun together. We believe in co-ownership and aligned incentives, so team members can become shareholders of the company. Learn more about our ways of work, and values on our website: https://planting.space/
