Research Scientist: AI Foundations & World Models in Cambridge

Research Scientist: AI Foundations & World Models in Cambridge

Cambridge Full-Time 60000 - 80000 € / year (est.) No home office possible
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At a Glance

  • Tasks: Conduct groundbreaking research in AI, focusing on world models and reasoning.
  • Company: Join Basis, a nonprofit at the forefront of applied AI research.
  • Benefits: Competitive salary, mentorship opportunities, and a collaborative work environment.
  • Other info: Work in-person in NYC or Cambridge, with a vibrant team culture.
  • Why this job: Make a real-world impact by solving complex problems with innovative AI solutions.
  • Qualifications: PhD in relevant fields and strong background in AI and machine learning.

The predicted salary is between 60000 - 80000 € per year.

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.

Research Focus

Despite the increasing recognition that both having and discovering world models are central to intelligence, current AI systems struggle to replicate this human capability. There remains significant uncertainty about what precisely constitutes a world model, how we might reliably detect if an agent possesses one, and crucially, how we can develop agents that learn these models rapidly and reliably. Our research within the MARA project aims to develop new foundations and technologies for modeling, abstraction, and reasoning in AI systems. MARA’s overarching goal is to uncover principled methods for how intelligence constructs, refines, and utilizes world models through interactive experimentation. Building these systems will demand advances in knowledge representation, abstraction, reasoning, active learning, reinforcement learning, and a first-principles rethinking of what it means to model the world. The immediate mission of MARA is to solve concrete challenges such as AutumnBench, physical and simulated robotics benchmarks, and the Abstract Reasoning Corpus (ARC), 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.

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.
  • Excited about solving real world problems and having positive societal impact.

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 AutumnBench, physical and simulated robotics environments, the Abstract Reasoning Corpus (ARC), and other domains.
  • Disseminate research findings through academic publications and presentations at leading conferences.
  • Provide mentorship to junior team members and contribute to the scientific discourse through seminars, workshops, and collaborative projects.
  • Develop and maintain open-source software.
  • (Optionally) Publish and present findings in journals and conferences.
  • 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.
  • In-person Policy: We are in the office four days a week. 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.
  • 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.

Research Scientist: AI Foundations & World Models in Cambridge employer: basis-research

Basis is an exceptional employer that fosters a collaborative and innovative work culture, where research scientists are encouraged to explore foundational concepts in AI while contributing to meaningful societal advancements. With a strong emphasis on employee growth, mentorship opportunities, and a commitment to high-quality scientific research, Basis provides a supportive environment for individuals passionate about solving complex problems. Located in vibrant cities like New York City and Cambridge, MA, employees benefit from a dynamic atmosphere that inspires creativity and collaboration.

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Contact Detail:

basis-research Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Scientist: AI Foundations & World Models in Cambridge

Tip Number 1

Network like a pro! Reach out to people in the AI research community, attend relevant meetups or conferences, and don’t be shy about introducing yourself. You never know who might have a lead on your dream job at Basis!

Tip Number 2

Show off your passion for foundational AI research! When you get the chance to chat with potential employers, share your thoughts on world models and how they relate to your work. This will help you stand out as someone who truly gets the field.

Tip Number 3

Prepare for interviews by diving deep into the MARA project and its challenges. Think about how your skills in program synthesis or cognitive modeling can contribute to their goals. Tailor your examples to show you’re ready to tackle real-world problems.

Tip Number 4

Don’t forget to 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 Basis team and contributing to their mission.

We think you need these skills to ace Research Scientist: AI Foundations & World Models in Cambridge

PhD in computer science, artificial intelligence, machine learning, cognitive science, or related fields
Program synthesis
Probabilistic programming
Machine learning
AI reasoning systems
Cognitive modeling
Development of AI systems combining neural and symbolic methods

Some tips for your application 🫡

Show Your Passion for AI:When writing your application, let your enthusiasm for AI and foundational research shine through. We want to see how excited you are about tackling complex problems and pushing the boundaries of what's possible in AI.

Highlight Relevant Experience:Make sure to showcase your background in areas like program synthesis, machine learning, and cognitive science. We’re looking for candidates with a solid track record, so don’t hold back on mentioning your publications or impactful projects!

Be Collaborative:Since we value teamwork, emphasise your experience working collaboratively on research projects. Share examples of how you've contributed to team efforts and how you enjoy solving problems together with others.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures that it gets into the right hands. Plus, it shows you’re serious about joining our team!

How to prepare for a job interview at basis-research

Know Your Foundations

Make sure you have a solid grasp of the mathematical principles behind AI and intelligence. Brush up on concepts like reasoning, learning, and decision-making, as these will likely come up in your interview. Being able to discuss these topics confidently will show that you’re not just technically excellent but also deeply understand the field.

Showcase Your Research Experience

Prepare to discuss your past research projects in detail. Highlight any publications or impactful software you've developed, especially those related to AI systems, program synthesis, or cognitive modeling. This is your chance to demonstrate your track record and how it aligns with the goals of the MARA project.

Emphasise Collaboration Skills

Since Basis values collaboration, be ready to share examples of how you've worked effectively in teams. Discuss any mentorship roles you've taken on or collaborative projects you've been part of. This will illustrate your ability to contribute positively to the team dynamic and tackle larger problems together.

Prepare for Problem-Solving Scenarios

Expect to engage in discussions about real-world challenges, such as those related to AutumnBench or robotics benchmarks. Think through how you would approach these problems and be prepared to articulate your thought process. This will showcase your practical application of theoretical knowledge and your excitement for solving complex issues.