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Research Scientist in Program Synthesis & Neuro-symbolic Methods

BasisNew York Office
On-site Full-time

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Experience Level

Experience

Qualifications

We expect you to:Demonstrate a proven track record of high-quality scientific research. This could include publications in top-tier venues (NeurIPS, ICML, ICLR, POPL, PLDI), technical reports, and notable software projects. Exhibit profound expertise in Program Synthesis and Neuro-symbolic Methods, combining theoretical insights with practical application. Collaborate effectively with team members and external partners to address complex research challenges.

About the job

About Basis

Basis is a pioneering nonprofit organization dedicated to applied AI research, pursuing two interconnected goals.

Our primary objective is to understand and create intelligence. This involves formulating the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation, while developing software that embodies these concepts.

The second goal is to enhance society’s capacity to solve complex challenges. We aim to broaden the scope, intricacy, and variety of challenges we can address today, and crucially, to expedite our ability to tackle future problems.

To realize these objectives, we are constructing an innovative technological base inspired by human reasoning, and fostering a collaborative organizational culture that prioritizes human values.

About the Role

As a Research Scientist on the MARA (Modeling, Abstraction, and Reasoning Agents) initiative, you will be instrumental in developing computational theories of scientific reasoning in the realms of robotics and embodied intelligence. Your work will push the boundaries of world modeling, reinforcement learning, program synthesis, and robotic control, enabling systems to learn, reason about, and engage with the physical world.

We are seeking outstanding researchers with a strong background in Program Synthesis & Neuro-symbolic Methods. The ideal applicant will have a robust publication record in esteemed venues, blending theoretical expertise with practical implementation skills, and a passion for building systems that emulate scientific learning—hypothesizing, experimenting, and modeling the workings of the world.

In this role, you will collaborate with an interdisciplinary team to address fundamental inquiries: How can agents learn causal models through interaction? How do we connect high-level reasoning with low-level control? How can we produce interpretable, verifiable control programs instead of opaque policies?

At Basis, we value collaboration, both within our team and with external partners; we seek individuals who thrive in teamwork on significant challenges that require collective effort.

About Basis

Basis is a forward-thinking nonprofit research organization specializing in applied AI, committed to fostering intelligence and enhancing society's problem-solving capabilities through innovative technology and collaborative efforts.

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