Research Scientist, Reinforcement Learning

About the role

This role is part of the MARA project at Basis, a nonprofit applied AI research organization. The primary focus is on advancing the state of the art in model-based reinforcement learning, exploration strategies, optimal control, and Bayesian optimization.

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

• PhD in computer science, artificial intelligence, machine learning, cognitive science, or related fields.
• 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.
• Demonstrated track record in scientific research, evidenced through publications, technical reports, or impactful software projects.
• Excited about solving real world problems and having positive societal impact.