At a Glance
- Tasks: Conduct groundbreaking research in AI, focusing on modeling, abstraction, and reasoning.
- Company: Join the innovative Basis Research Institute and Cornell University’s Ellis Lab.
- 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 shape the future of technology.
- Qualifications: PhD in relevant fields with strong AI and machine learning background.
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.
Postdoctoral Fellow, MARA (Modeling, Abstraction and Reasoning Agents) 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 cutting-edge research alongside esteemed colleagues at Cornell University, with ample opportunities for professional growth, mentorship, and impactful contributions to the MARA project. The unique setting in Ithaca, NY, combined with periodic engagements in New York City, fosters a dynamic culture of knowledge exchange and community building.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Fellow, MARA (Modeling, Abstraction and Reasoning Agents) in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and cognitive science communities, especially those connected to Cornell or Basis. 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 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 MARA project.
✨Tip Number 3
Be proactive! Don’t just wait for job openings to pop up. Reach out directly to Kevin Ellis’s lab or the Basis Research Institute to express your interest in the fellowship. A personal touch can make all the difference!
✨Tip Number 4
Stay updated on the latest in AI research. Follow relevant journals, blogs, and social media accounts. Being well-informed will not only help you in interviews but also show your genuine passion for foundational AI research.
We think you need these skills to ace Postdoctoral Fellow, MARA (Modeling, Abstraction and Reasoning Agents) 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 your passion for AI and how you can contribute to our goals!
Showcase Your Research:Include details about your previous research, publications, or projects that relate to AI, cognitive science, or machine learning. This is your chance to shine, so let us know what you've achieved!
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon and make sure your ideas come across clearly.
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.
How to prepare for a job interview at basis-research
✨Know Your Research Inside Out
Make sure you’re well-versed in your own research and how it relates to the MARA project. Be prepared to discuss your previous work, especially any publications or projects that showcase your expertise in AI, machine learning, or cognitive science.
✨Familiarise Yourself with the Team's Work
Take some time to read up on Kevin Ellis’s research and the specific areas his lab focuses on. Understanding their approach to AI systems and how they integrate neural and symbolic methods will help you align your answers with their goals during the interview.
✨Prepare for Technical Questions
Expect to face technical questions related to program synthesis, probabilistic programming, and AI reasoning systems. Brush up on these topics and think of examples from your past work that demonstrate your skills and problem-solving abilities.
✨Show Enthusiasm for Collaboration
This fellowship is all about teamwork and collaboration. Be ready to discuss how you’ve worked with others in the past and express your excitement about contributing to a multidisciplinary team at Basis and Cornell University.