Research Fellow (1-Year): Technology, Work, and Economic Change

Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!Location: Flexible / RemoteDuration: 12 months (with possibility of extension)Why this role?Cohere Labs is the dedicated research arm of Cohere. Our mission is to tackle foundational questions in artificial intelligence by bringing together researchers across disciplines to study not only how AI systems are built, but how they reshape economies, labor markets, and institutions.As AI technologies rapidly diffuse into the economy, there is an urgent need for rigorous, theory-informed, and empirically grounded research on their implications for productivity, inequality, skills, organizational design, and the future of work. This role is designed to create space for exactly that kind of work.The Research Fellow (Future of Work & AI) position is a 1-year, full-time research appointment aimed at advanced PhD students, postdocs, or early-career researchers in economics, political economy, public policy, or related social sciences who want to engage deeply with frontier AI systems while maintaining scholarly independence and publication-oriented research.What makes this role uniqueDesigned for economists, not engineers: No expectation that you are an ML practitioner, intellectual curiosity and analytical rigor matter mostResearch-first: Time and support to write, think, and publishInterdisciplinary exposure: Work alongside leading AI researchers while maintaining disciplinary depthSocietal relevance: Direct engagement with questions shaping policy, labor, and economic futuresGlobal perspective: Opportunity to study impacts beyond high-income, English-speaking contextsYou are likely a strong fit if you haveA PhD (or are an advanced PhD candidate) in Economics, Political Economy, Public Policy, or a closely related fieldStrong training in economic theory, econometrics, or applied micro / macroA demonstrated research interest in technology, innovation, labor, growth, or institutionsA publication record (or pipeline) in peer-reviewed academic venuesAn interest in engaging seriously with AI systems and their real-world deploymentA desire to collaborate across disciplines while retaining intellectual independenceYou may be especially excited about this role if youWant to study AI as a general-purpose technology, not just a toolEnjoy connecting theory to emerging empirical realitiesCare about the long-run societal consequences of technological changeAre interested in shaping conversations at the intersection of academia, industry, and policyValue mentorship, open science, and collaborative research culturesIf some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the c ... (truncated, view full listing at source)