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Research Scientist, Robotics
Research Scientist, RoboticsBasis Research • New York, NY, United States
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Research Scientist, Robotics

Research Scientist, Robotics

Basis Research • New York, NY, United States
[job_card.30_days_ago]
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  • [job_card.full_time]
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About Basis

Basis is a nonprofit applied AI research organization with two mutually reinforcing goals.

The first is to understand and build intelligence. This means to establish the mathematical principles of what it means to reason, to learn, to make decisions, to understand, and to explain; and to construct software that implements these principles.

The second is to advance society's ability to solve intractable problems. This means expanding the scale, complexity, and breadth of problems that we can solve today, and even more importantly, accelerating our ability to solve problems in the future.

To achieve these goals, we're building both a new technological foundation that draws inspiration from how humans reason, and a new kind of collaborative organization that puts human values first.

About the Role

Research scientists lead Basis' efforts to develop a deeper understanding of the conceptual, mathematical, and computational principles of intelligence.

We are looking for people who are technically excellent, and who value probing concepts at their foundations. Our research scientists/engineers aspire to do rigorous, high-quality, robust science, but are not afraid to tinker, make mistakes, and explore radically different ideas in order to get there.

Basis is a collaborative effort, both internally and with our external partners; we are looking for people who enjoy working with others on problems larger than ones they can tackle alone.

Robotics projects at Basis

We are searching for robotics expertise across multiple projects, both active and in development.

Active projects:
  1. MARA - Modeling, Abstraction & Reasoning Agents
Science advances by discovering useful abstractions. MARA operationalizes this insight into software agents. Instead of passively absorbing data, MARA agents propose hypotheses, run physical or simulated experiments, and revise models of the world until a compact, coherent theory emerges. Early results show MARA systems solving previously unresolved (ARC) Abstraction and Reasoning Corpus tasks; widely considered among the hardest AI benchmarks today. We are opening a new branch of the project to bring MARA into the physical world, with embodied agents that learn from experience, build internal representations, and apply "everyday science" human-like reasoning to solve problems.

Read the latest from MARA on our blog.
  1. R-ADA - a Rational Automated Design Agent

R-ADA aims to automate robotics, co-designing robot morphology (hardware) with controllers (software). We are treating the robot design as a sequential decision process, akin to human designers. A multimodal reasoning system designs robots as CAD programs, deploying both tools (e.g. FEM analysis) and internal world models, to understand what changes it should make and why. Candidate robots are evaluated in simulation using cross-morphology meta-policies, efficiently estimating their optimal performance across various tasks. A probabilistic back-end updates its understanding of the physics gap with every real-world test. The payoff is a pipeline to quickly design optimal robots tailored to specific tasks, on the fly.

We expect you to:
  • Have a PhD (or equivalent research experience) in a relevant area such as Robotics, Computer Science, Electrical Engineering, or a related quantitative field.
  • Have hands-on experience with real-world robots, including:
    • Working with robotic hardware, APIs, and real-time control systems.
    • Integrating and utilizing camera systems and other sensors for robotic perception.
    • Developing and deploying robotic control policies for manipulation tasks.
  • Have experience with relevant aspects of machine learning for robotics, particularly some of the following:
    • Deep learning architectures for vision and language processing in robotics.
    • Imitation learning and reinforcement learning for robotic control.
    • Techniques for robust generalization to unseen tasks, objects, and environments.
  • Have demonstrated an ability to conduct first-class scientific research, published in venues such as CoRL, ICRA, RSS, NeurIPS, ICML, or in technical reports.
  • Have demonstrated an ability to write excellent software.
  • Be excited about solving real-world problems and having a positive societal impact.
Responsibilities
  • Contribute to the design, implementation, and deployment of foundational robotic control systems.
  • Collaborate with domain experts on Basis scientific and societal challenge problems involving robotic interaction.
  • Collaborate with domain experts on Basis scientific and societal challenge problems.
  • Develop and maintain open-source software.
  • Publish and present findings in journals and conferences (optional).
  • Contribute to the culture and direction of Basis.
Role Details

Exceptional candidates who may not meet all of the following criteria are still encouraged to apply.
  • FT/PT: This is a full-time position.
  • Hours: While we prioritize in-person collaboration for its benefits to creative work, there is a degree of flexibility in your working hours. Expect to be available during certain set times each week for meetings, and be prepared to attend multi-day Basis-wide in-person events.
  • Location: This role is in-person in either New York City or Cambridge, MA.
  • Salary range: Competitive salary and bonuses.


Privacy Notice

By submitting your application, you grant Basis permission to use your materials for both hiring evaluation and recruitment-related research and development purposes. Your information may be processed in different countries, including the US. You retain copyright while providing Basis a license to use these materials for the stated purposes.

Read our full Global Data Privacy Notice here.
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