Basis is looking to develop a deeper understanding of the conceptual, mathematical, and computational principles of intelligence and to advance society’s ability to solve intractable problems by developing new foundations and technologies for modeling, abstraction, and reasoning in AI systems.
Requirements
- Strong background in reinforcement learning, planning, MDPs, optimal control, and sequential decision making.
- Experience in developing AI systems that combine neural and symbolic methods is highly valued.
- Interest in foundational AI research and its applications to modeling, abstraction, and reasoning.
- Individuals with a demonstrated track record in scientific research, evidenced through publications, technical reports, or impactful software projects.
- Experts in Reinforcement Learning & Planning who can advance the state of the art in model-based RL, exploration strategies, optimal control, and Bayesian optimization.
- Developing agents that can learn efficient policies in complex, partially observable environments by leveraging structured world models.
Responsibilities
- Conduct independent and collaborative research focused on the MARA project.
- Develop new methods and algorithms for reinforcement learning, planning, and decision-making in AI systems.
- Apply these methods to concrete challenges such as AutumnBench, physical and simulated robotics environments, and other domains.
- Disseminate research findings through academic publications and presentations at leading conferences.
- Provide mentorship to junior team members and contribute to the scientific discourse through seminars, workshops, and collaborative projects.
- Develop and maintain open-source software
- (Optionally) Publish and present findings in journals and conferences
Other
- Researchers holding a PhD in computer science, artificial intelligence, machine learning, cognitive science, or related fields.
- Excited about solving real world problems and having positive societal impact.
- This is a full-time position
- We are in the office four days a week. Be prepared to attend multi-day Basis-wide in-person events.
- This role is in-person in either New York City or Cambridge, MA.
