Research Scientist, Reinforcement Learning

About the role

Research scientists lead Basis’ efforts to develop a deeper understanding of the conceptual, mathematical, and computational principles of intelligence. They aim to establish the mathematical principles of reasoning, learning, decision-making, understanding, and explanation, and to construct software that implements these principles. Additionally, they focus on advancing society's ability to solve intractable problems by expanding the scale, complexity, and breadth of problems that can be solved today and in the future.

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.

Qualifications

• Holding a PhD in computer science, artificial intelligence, machine learning, cognitive science, or related fields.
• A 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.
• An interest in foundational AI research and its applications to modeling, abstraction, and reasoning.
• A demonstrated track record in scientific research, evidenced through publications, technical reports, or impactful software projects.
• Excitement about solving real-world problems and having a positive societal impact.