At a Glance
- Tasks: Conduct groundbreaking research in reinforcement learning and AI systems.
- Company: Join a nonprofit AI research organisation focused on solving real-world problems.
- Benefits: Competitive salary, mentorship opportunities, and a collaborative work environment.
- Other info: Work in-person in NYC or Cambridge, with excellent career growth potential.
- Why this job: Make a positive societal impact while exploring the foundations of intelligence.
- Qualifications: PhD in relevant fields and strong background in reinforcement 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
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. For this role, we are specifically looking for experts in Reinforcement Learning & Planning who can advance the state of the art in model-based RL, exploration strategies, optimal control, and Bayesian optimization. You will work on developing agents that can learn efficient policies in complex, partially observable environments by leveraging structured world models. 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 reinforcement learning, planning, MDPs, optimal control, and sequential decision making.
- 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 reinforcement learning, planning, and decision-making in AI systems.
- Apply these methods to concrete challenges such as AutumnBench, physical and simulated robotics environments, 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.
Research Scientist, Reinforcement Learning in Cambridge employer: basis-research
Basis is an exceptional employer that fosters a collaborative and innovative work culture, prioritising human values while tackling complex societal challenges through applied AI research. Employees benefit from competitive salaries, opportunities for mentorship, and the chance to contribute to groundbreaking projects in a supportive environment located in vibrant cities like New York City or Cambridge, MA. With a focus on personal and professional growth, Basis encourages researchers to explore foundational concepts and engage in meaningful scientific discourse.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist, Reinforcement Learning in Cambridge
✨Tip Number 1
Network like a pro! Reach out to people in the AI and reinforcement learning community. Attend meetups, conferences, or even online webinars. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to reinforcement learning and AI. This is your chance to demonstrate your expertise and passion for the field.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as collaboration is key at Basis. We want to see how you think!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of our mission to advance AI for societal good.
We think you need these skills to ace Research Scientist, Reinforcement Learning in Cambridge
Some tips for your application 🫡
Show Your Passion for AI:When writing your application, let us see your enthusiasm for AI and reinforcement learning. Share your experiences and projects that highlight your interest in foundational research and how it can solve real-world problems.
Be Specific About Your Skills:We want to know what makes you a great fit for the role! Detail your expertise in reinforcement learning, planning, and any relevant algorithms you've worked on. The more specific you are, the better we can understand your background.
Highlight Collaborative Experiences:Since we value collaboration, mention any teamwork or partnerships you've had in your research. Talk about how you’ve contributed to group projects and what you learned from working with others in the field.
Apply Through Our Website:Make sure to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at basis-research
✨Know Your Reinforcement Learning Stuff
Make sure you brush up on your reinforcement learning concepts, especially model-based RL and optimal control. Be ready to discuss your past projects and how they relate to the challenges at Basis. They’ll want to see your depth of knowledge and how you can apply it to real-world problems.
✨Show Off Your Collaborative Spirit
Basis values collaboration, so be prepared to share examples of how you've worked with others in the past. Highlight any experiences where you tackled complex problems as part of a team. This will show that you’re not just a lone wolf but someone who thrives in a collaborative environment.
✨Prepare for Technical Questions
Expect some tough technical questions during the interview. Brush up on your algorithms, decision-making processes, and any relevant mathematical principles. Practising coding problems or discussing theoretical scenarios can help you feel more confident when faced with these questions.
✨Demonstrate Your Passion for AI Research
Let your enthusiasm for foundational AI research shine through. Talk about what excites you about the field and how you see it evolving. Mention any recent papers or breakthroughs that have inspired you, and be ready to discuss how you can contribute to Basis's mission of solving intractable problems.
