At a Glance
- Tasks: Conduct groundbreaking research in AI reasoning and modeling for the MARA project.
- Company: Join Basis, a nonprofit AI research organisation partnered with Cornell University.
- Benefits: Competitive salary, mentorship opportunities, and a collaborative research environment.
- Other info: Full-time position with opportunities for travel and professional growth.
- Why this job: Make a real impact in foundational AI research and solve complex problems.
- Qualifications: PhD in relevant fields and strong background in AI and machine learning.
The predicted salary is between 35000 - 45000 £ per year.
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.
Postdoc, MARA: AI Reasoning & Modeling in Cambridge employer: basis-research
Basis Research Institute is an exceptional employer for those passionate about advancing AI technologies, offering a collaborative and innovative work environment that prioritises human values. As a Postdoctoral Fellow, you will engage in groundbreaking research alongside esteemed colleagues at Cornell University, with ample opportunities for professional growth, mentorship, and contributions to impactful projects. The unique setting of Ithaca, NY, combined with the dynamic atmosphere of New York City, provides a stimulating backdrop for both personal and academic development.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoc, MARA: AI Reasoning & Modeling in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and cognitive science communities, especially those connected to the MARA project. Attend conferences, workshops, or even local meetups to make connections that could lead to opportunities.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your past research, publications, and any impactful software projects. When you get the chance to chat with potential collaborators or interviewers, share your work and how it aligns with the goals of the MARA project.
✨Tip Number 3
Be proactive! Don’t just wait for job openings to pop up. Reach out directly to the Basis Research Institute or Kevin Ellis’ lab to express your interest in their work. A well-timed email can set you apart from the crowd.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the team and contributing to the exciting work at Basis and Cornell University.
We think you need these skills to ace Postdoc, MARA: AI Reasoning & Modeling in Cambridge
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your application to highlight how your skills and experiences align with the MARA project. We want to see how you can contribute to our goals, so don’t hold back on showcasing your relevant expertise!
Showcase Your Research:Include details about your past research, especially any publications or projects that relate to AI reasoning and modeling. We love seeing a strong track record, so make it easy for us to see your impact in the field!
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that are easy to read. Avoid jargon unless it’s necessary, and make sure your passion for foundational AI research shines through!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your materials and ensures you’re considered for this exciting opportunity. We can’t wait to hear from you!
How to prepare for a job interview at basis-research
✨Know Your Research
Dive deep into the MARA project and its goals. Familiarise yourself with the latest advancements in AI reasoning and modeling, especially those related to cognitive science and program synthesis. This will not only show your genuine interest but also help you engage in meaningful discussions during the interview.
✨Showcase Your Experience
Prepare to discuss your previous research and projects that align with the fellowship's focus. Highlight any experience you have with neural-symbolic integration or developing AI systems. Be ready to explain how your work can contribute to the ambitious goals of the MARA project.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the research environment, collaboration opportunities, and the specific challenges the team is facing. This demonstrates your enthusiasm and helps you assess if the role is the right fit for you.
✨Emphasise Collaboration
Since the role involves working closely with a team, be sure to highlight your collaborative skills. Share examples of how you've successfully worked in teams before, particularly in research settings. This will reassure them that you can thrive in their structured yet adaptable environment.
