---
title: 'Postdoctoral Fellow, MARA (Modeling, Abstraction and Reasoning Agents) at Basis Research Institute'
canonical: 'https://feeny.ai/job/postdoctoral-fellow-mara-modeling-abstraction-and-reasoning-agents-basis-j30ds47gd101'
type: 'job'
last_seen: '2026-09-10'
---

# Postdoctoral Fellow, MARA (Modeling, Abstraction and Reasoning Agents) at Basis Research Institute

- **Company:** Basis Research Institute
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-02-03
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/basis-research/438aa3f2-1aaf-4bd6-93e6-6b6c9042d926

## Job description

## About the Fellowship

This Basis Postdoctoral Fellowship is a collaborative initiative between the Basis Research Institute and Cornell University's [Ellis Lab](https://www.cs.cornell.edu/~ellisk/). 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](https://www.basis.ai) 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](https://www.cs.cornell.edu/~ellisk/) 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](https://www.basis.ai/join-us/privacy-notice/).

## About Basis Research Institute

## Company Overview
- **One-liner**: Basis Research Institute is a nonprofit applied research organization advancing artificial intelligence through probabilistic modeling and causal inference to solve society's most intractable problems, building open-source software that draws inspiration from human reasoning.
- **Entity Type**: Private (Nonprofit 501(c)(3) Research Institute)
- **Headquarters**: New York City, New York, USA (with additional office in Cambridge, Massachusetts, USA)
- **Founded**: 2022
- **Founders**: Zenna Tavares, Emily Mackevicius, and Eli Bingham

## Core Business
- **Primary industry**: Artificial Intelligence Research & Development
- **Target customers**: Municipal governments (via consulting), academic collaborators, for-profit companies (via contract work), and the broader open-source AI community
- **Mission**: Two mutually reinforcing goals: (1) advance basic scientific research in artificial intelligence to understand and build intelligence, and (2) help solve society’s intractable problems by expanding the scale, complexity, and breadth of problems that can be solved

## Products & Services
- **Core Technology Development**: Advanced probabilistic modeling and causal inference frameworks implemented as open-source software, including causal probabilistic programming languages
- **Applied Challenge Projects**:
  - **AI-Driven Robot Design**: Using AI to automate and accelerate robot design and control
  - **Dynamical Modeling for Biological Systems**: Modeling complex biological processes (e.g., neuroscience, cellular dynamics)
  - **Participatory City Modeling**: Consulting with municipal governments to model urban systems and support data-driven policy decisions
  - **Modeling, Abstraction, and Reasoning Agent (MARA)**: A research project focused on building AI agents capable of abstract reasoning and world modeling
- **Postdoctoral Fellowship Program**: A fellowship for early-career scientists to direct their own research within Basis’s mission
- **Open-Source Software Releases**: Publishing research tools and libraries for the broader AI community

## Market Standing
- **Valuation/Market Cap**: Not applicable (nonprofit research organization)
- **Key Metric**: Funded through a combination of research grants, private philanthropy, and contract work with partners; specific funding amounts are not publicly disclosed
- **Notable Investors/Partners**: Supported by an advisory board including Armando Solar-Lezama (MIT), Joshua Tenenbaum (MIT), Kevin Ellis (Cornell), Anthony Philippakis (Broad Institute), and Rui Costa (Columbia University). Collaborates with academic institutions (MIT, Columbia, Cornell, NYU) and municipal governments
- **Growth Signals**: Headcount has grown 41.7% year-over-year (LinkedIn data); active job postings increased 107.1% year-over-year; expanding into London with a GTM Lead role; 29 active job openings as of mid-2026

## Competitive Advantages
- **Nonprofit Structure**: Unlike for-profit AI labs, Basis is a 501(c)(3) nonprofit, enabling it to prioritize open-source, public-good research over commercial outcomes
- **Unique Research Cycle**: A structured cycle between core technology development and applied challenge projects, where insights from real-world problems feed back into foundational research
- **Interdisciplinary Approach**: Combines insights from cognitive science (human reasoning), computer science (probabilistic programming), and domain expertise (biology, urban planning, robotics)
- **High-Profile Advisory Board**: Advisors from leading institutions (MIT, Cornell, Broad Institute, Columbia) provide deep academic and scientific credibility
- **Open-Source Commitment**: All software is released as open-source, building community trust and enabling broad adoption

## Strategic Focus
- **Core AI Foundations**: Advancing probabilistic modeling, causal inference, program synthesis, neuro-symbolic methods, reinforcement learning, and world models
- **Challenge-Driven Research**: Using applied projects (robotics, biology, city modeling) to identify shared bottlenecks that guide further methodological research
- **Collaborative Expansion**: Actively seeking partnerships with academia, government, social sector, and industry to tackle high-impact problems
- **Geographic Growth**: Opening presence in London (UK/EU GTM) and expanding roles in Ithaca, NY, while maintaining NYC and Cambridge hubs
- **Open-Source Ecosystem**: Building durable foundations that enable other researchers and practitioners to build upon Basis’s work

## Why Work Here
- **Mission-Driven Culture**: Employees work on problems that matter beyond publications, with impact on AI science and real-world societal challenges
- **Autonomy and Growth**: Organizational structure allows employees to see their autonomy and responsibilities grow with their projects, distinct from traditional career ladders
- **Collaborative Environment**: Work alongside researchers from top institutions (MIT, Columbia, Cornell) and domain experts from academia, government, and industry
- **Open-Source Impact**: Ship high-quality open-source software used by thousands, contributing to the broader AI community
- **Locations**: Offices in NYC (primary) and Cambridge, MA, with remote flexibility for some roles; London expansion underway
- **Notable Perks**: Postdoctoral fellowships available for early-career scientists; focus on human values and collaborative organization
- **Engineering Culture**: Emphasis on building durable foundations, shipping production-quality code, and working at the intersection of research and engineering

## Sources
1. [basis.ai/about](https://www.basis.ai/about/)
2. [basis.ai](https://www.basis.ai/)
3. [jobs.ashbyhq.com/basis-research](https://jobs.ashbyhq.com/basis-research)
4. [basis.ai/join-us](https://www.basis.ai/join-us/)
5. [LinkedIn - Basis Research Institute](https://www.linkedin.com/company/basis-ri)

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