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Physical Superintelligence

AI for physics problem-solving platform

Member of Technical Staff - Physics Research

Physical SciencesUpdated on Nov 6
Full-timeCambridge, MA, USA

About the Job

Requirements

  • Have three or more years of research experience and publications in top-tier journals in one area of fundamental physics.
  • Demonstrate rigor in deriving and checking results, distinguishing numerical hints from proofs and signals from setup artifacts, and using exact or semidefinite programming certificates, interval arithmetic, computer algebra, proof assistants, or large-scale numerical experiments when appropriate.
  • Have three or more years of hands-on experience at the intersection of physics and machine learning, including using machine learning or artificial intelligence systems on a physics problem, training or directing a model, reading modern machine learning papers, reasoning about agent behavior, and evaluating outputs.
  • Have deep expertise in one area of theoretical or experimental physics: quantum theory, many-body and condensed matter; statistical mechanics and complex systems; atomic, molecular and optical physics; high energy, particle and nuclear physics; gravity and cosmology; or mathematical physics.

Responsibilities

  • Run research programs on open problems in the candidate's area, formulate the problems, direct AI systems at them, evaluate the results, and take ownership of the outcome.
  • Encode what constitutes a correct physics answer so that it is legible to machines, verify AI output against those criteria, and stand behind results before publication or release.
  • Write manuscripts and own the path to publication, collaborating with AI researchers on how agents reason about physics.

Desired Qualifications

  • Strong Python skills, including production code experience rather than notebook-only work.
  • Results on named open problems or conjectures in the candidate's field.
  • Experience converting physics problems into machine-verifiable tasks or building benchmark or verification systems for physics or mathematics results.
  • Experience refereeing for top journals.

About the Company

Physical Superintelligence

AI for physics problem-solving platform

Physical Superintelligence (PSI) builds AI tools for physics through its Emmy platform, which runs virtual physicists on a reasoning engine and curated simulations to decompose problems into verifiable hypotheses and test them in parallel. This enables solving physics-based challenges by generating, evaluating, and validating multiple hypotheses at once. Unlike broader AI firms, PSI focuses on physics applications, offering a verified, simulation-driven workflow and pursuing real-world deployments such as optimizing terrestrial and orbital AI data centers, and acting as the founding technical partner for an interstellar mission. PSI is structured as a public benefit corporation, guiding its growth with a mission to advance physics-driven AI while delivering tangible, tested results for complex scientific and engineering problems.

Company size
1-10
Company stage
Seed
Total funding
$58M
Headquarters
Cambridge, MA
Founded
2025

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