We are building an AI system for analysts and scientists, based on a fundamentally new approach to reasoning and knowledge representation. We go beyond state-of-the-art LLMs by combining algorithms in symbolic ways, to provide novel capabilities like performing multi-step analysis, displaying a verifiable reasoning path, and assessing uncertainty. We envision applications supporting and automating analysis and research in domains such as Finance, Strategy Consulting, Engineering, Material Sciences, and more.
We are looking for
full-time researchers to contribute to the development and analysis of our learning algorithm
. 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
- Advanced mathematical analysis methods, for example: mathematical statistics, optimal transport, information geometry, optimization methods, and dynamical systems
- Translation between equational reasoning and code implementation
- Hierarchical Bayesian modeling and Bayesian computation
- Meta learning or transfer learning
- Research software engineering, algorithm development, and prototyping from scratch
- Mathematics, Computer Science, or Statistics advanced degree (ideally PhD)
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/Apply for this job
