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Basis Research Institute

Postdoctoral Fellow, MARA (Modeling, Abstraction and Reasoning Agents)

Basis Research Institute is hiring a Postdoctoral Fellow, MARA (Modeling, Abstraction and Reasoning Agents) in New York, United States. It pays $100k a year and Level rates it ; you can apply on Basis Research Institute.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • The posting mentions AI research among its tools and skills.
  • Basis Research Institute has 12 other open roles on Level.

AI in this role

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About the Fellowship

This Basis Postdoctoral Fellowship is a collaborative initiative between the Basis Research Institute and Cornell University's Ellis Lab. As a fellow, you will be a key contributor to our ambitious MARA (Modeling, Abstraction, and Reasoning Agent) project, which aims to develop foundational AI technologies that enable systems to actively discover abstract models of the world and reason with them to achieve goals.

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 Kevin Ellis’ Group

Kevin Ellis is an Assistant Professor in the Computer Science department at Cornell University. His research focuses on artificial intelligence, program synthesis, and the intersection of AI and cognitive science. The Ellis Lab explores how to build AI systems that learn and reason like humans, particularly in areas such as programming by example, world modeling, neural-symbolic integration, and few-shot learning. The group combines techniques from machine learning, program synthesis, probabilistic programming, and cognitive science to develop AI systems that can learn complex tasks from limited data and generalize across domains.

Research Focus

Our research aims to develop new foundations and technologies for modeling, abstraction, and reasoning in AI systems, focusing on the MARA project. MARA's general goal is to build systems that actively discover abstract models of the world and reason with these models to carry out goals. Building these systems will demand advances in knowledge representation, abstraction, reasoning, active learning, and a first-principles rethinking of what it means to model the world.

The immediate mission of MARA is to solve the Abstract Reasoning Corpus (ARC) in a way that generalizes to other domains, with the broader mission of building systems capable of learning in an open, growing portfolio of domains using human-comparable amounts of data and interaction.

Fellows will have the opportunity to contribute to this ambitious project, working closely with a team of researchers at Basis and Cornell University. The research environment is both structured and adaptable, providing multiple avenues for scholarly contribution. As a fellow, your expertise can shape various aspects of the project, allowing for a balance of focused research, academic exploration, and software development.

Who we’re looking for

  • Researchers holding a PhD in computer science, artificial intelligence, machine learning, cognitive science, or related fields.

  • Strong background in areas such as program synthesis, probabilistic programming, machine learning, AI reasoning systems, and cognitive modeling.

  • 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.

  • Individuals with a demonstrated track record in scientific research, evidenced through publications, technical reports, or impactful software projects.

Core Responsibilities

  • Conduct independent and collaborative research focused on the MARA project.

  • Develop new methods and algorithms for modeling, abstraction, and reasoning in AI systems.

  • Apply these methods to concrete challenges such as the Abstract Reasoning Corpus (ARC) and other domains.

  • Disseminate research findings through academic publications and presentations at leading conferences.

  • Actively engage in knowledge transfer within Basis and Cornell University, converting research into actionable insights and algorithms.

  • Provide mentorship to junior team members and contribute to the scientific discourse through seminars, workshops, and collaborative projects.

Role Details

  • Full-time: This fellowship is full-time and has a fixed duration of 1 to 2 years.

  • Location: This is an in-person position, with time split between Ithaca, NY and NYC. You will have space at Kevin Ellis's lab at Cornell University and will collaborate closely with Basis Research Institute. You will be expected to travel periodically, about once every six to eight weeks, for Basis-wide in-person events, typically in New York City.

  • Salary: Competitive with leading postdoctoral fellowships.

  • Start date: Immediate start possible.

Non-Discrimination Notice
Basis Research Institute provides equal employment opportunities without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or genetics and prohibits discrimination based on all protected characteristics.

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.

How we rate this

Postdoctoral Fellow, MARA (Modeling, Abstraction and Reasoning Agents) at Basis Research Institute rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI Research

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

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  • List these exact terms on your resume: AI Research. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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