Research Scientist, Program Synthesis & Neuro-symbolic Methods

About the Company

Basis is a nonprofit applied AI research organization focused on understanding and building intelligence and advancing society's ability to solve intractable problems through a new technological foundation.

Responsibilities

• Develop computational theories of intelligence specific to program synthesis and neuro-symbolic methods
• Design and implement novel algorithms for sample efficiency, generalization, and interpretability in embodied AI
• Collaborate across specializations to integrate world modeling with planning and symbolic reasoning
• Validate research on physical systems by working with hardware engineers to address the sim-to-real gap
• Work with domain experts to identify impactful applications in scientific discovery and manufacturing
• Develop and maintain open-source software for reproducible research
• Publish and present findings in journals and conferences

Requirements

• Demonstrated ability to conduct high-quality scientific research (e.g., publications at NeurIPS, ICML, ICLR, POPL, PLDI)
• Deep expertise in Program Synthesis & Neuro-symbolic Methods, including DSLs and program induction
• Experience combining neural networks with symbolic reasoning or program generation
• Strong mathematical foundations in probability theory, optimization, and linear algebra
• Ability to implement complex algorithms from first principles
• Experience working across the research-to-deployment pipeline
• Ability to work autonomously and drive projects to completion

Preferred Qualifications

• PhD in robotics, machine learning, computer vision, control theory, cognitive science, or physics
• Experience at leading academic or industry robotics/AI labs
• Track record of algorithms deployed on physical robot systems
• Contributions to major open-source projects in robotics or ML
• Experience spanning both theoretical research and systems engineering