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ABOUT RESOLUTION Resolution does research on how to align artificial superintelligence (ASI). ASI may be developed in the next few years, but it is unclear whether alignment is on track to be ready in the same timeframe. We aim at higher a priori confidence in aligned outcomes by pursuing a portfolio of theory and empirics bets, any one of which — if it succeeds — would meaningfully advance the field. We invest heavily in research automation to accelerate progress, and we believe that stronger alignment theory unlocks higher automation: more principled approaches give us better filters for which directions of automated research are promising. Resolution was founded in 2026 by researchers from UK AISI's Alignment Team, who ran the £30m Alignment Project https://alignmentproject.aisi.gov.uk/, and Timaeus https://timaeus.co/, who pioneered applying singular learning theory to alignment. For more information, see our announcement https://sequent.org/launch. ABOUT THE TEAM We are hiring Research Scientists across our research programs. The team you'd join depends on your strengths and interests. In your application, indicate which program(s) you'd be most interested in. ABOUT THE ROLE As a Research Scientist at Resolution, you'll work as part of a research program led by a senior researcher (which could be you!). At Resolution, our goal of reaching higher confidence in alignment will require significant new contributions in both methods and scientific understanding. The work you do day-to-day will be part of a collaborative research program; all programs involve deep technical research, with strong support for cross-program collaboration. We welcome both empirical and theoretical profiles. RESPONSIBILITIES - Research within your program: both translating and modelling alignment problems into concrete empirical or theoretical form and executing on the resulting concrete problems. Execution means designing and running experimental protocols and methods for empirics, and proving, conjecturing, and investing in autoformalization for theory. - Writing and presentation of completed research in the form of papers, blog posts, and talks. - Communication of research progress and obstacles to members of your team through channels like Slack on a daily basis and in weekly meetings. YOU MAY BE A GOOD FIT IF YOU - Have a graduate degree (Ph.D.) or equivalent experience in a field relevant to the program you're applying to: ML, CS, mathematics, physics, statistics, philosophy, or something closely related - Have a track record of research and strong technical writing ability: papers, preprints, or comparable output - Have a strong mathematical background, even if your work is primarily empirical - Can credibly articulate why your area of alignment work is worth pursuing - Are willing to use AI tools aggressively in your own workflow, with appropriate care to not get fooled! - Are motivated by alignment of artificial superintelligence (ASI) and want to contribute to it full-time STRONG CANDIDATES MAY ALSO HAVE - (For scalable oversight) Hands-on experience with debate, prover-verifier games, RLHF empirics at frontier scale; familiarity with the scalable oversight literature; background in game theory, complexity theory, mechanism design, or decision theory - (For complexity theory) Demonstrated expertise in theoretical computer science, including creative modeling and assumption generation - (For learning theory) Background in algebraic geometry, Bayesian statistics, information theory, statistical physics, optimization theory, or learning theory; familiarity with (singular) learning theory - (Across programs) Experience scaling experiments to billion-plus parameter models; a track record of productive collaboration with engineers; prior engagement with our research or sibling organizations (Simplex, ARC, etc.). Experience with AI alignment is a plus, but is not a requirement: we are excited to bring