Research Scientist, Program Synthesis & Neuro-symbolic Methods

Responsibilities

• Develop computational theories of intelligence specific to program synthesis and neuro-symbolic methods, focusing on synthesizing control programs, learning interpretable models, or bridging symbolic reasoning with neural learning.
• Design and implement novel algorithms that push the boundaries of sample efficiency, generalization, interpretability, or robustness in embodied AI systems.
• Collaborate across specializations to integrate world modeling with planning, symbolic reasoning with neural learning, and high-level objectives with low-level control.
• Validate research on physical systems by working with hardware engineers to test algorithms on real robots, addressing the sim-to-real gap and practical deployment challenges.
• Work with domain experts inside and outside Basis to identify impactful applications of MARA technology in scientific discovery, manufacturing, or other domains.
• Distill insights from problem-solving into general mathematical and computational theories that advance our understanding of intelligence.
• Develop and maintain open-source software that enables reproducible research and broader community engagement with MARA technologies.

Qualifications

• PhD (or equivalent experience) in technical areas including: robotics, machine learning, computer vision, control theory, cognitive science, or physics.
• Experience at leading robotics or AI labs (academic or industry).
• Track record of algorithms deployed on physical robot systems.
• Contributions to major open-source projects in robotics or ML.
• Experience with both theoretical research and systems engineering.
• Background spanning multiple specialization areas.