About the job
Research Scientist in Physics
About Us
Physical Superintelligence is a pioneering startup with prestigious roots at Harvard, MIT, Johns Hopkins, Oxford, the Institute for Advanced Study, and the Perimeter Institute. We are on a mission to build AI systems that uncover new physics breakthroughs at scale. We invite talented physicists to join our team in crafting evaluation frameworks and verification systems that facilitate AI-driven discoveries in physics.
Key Responsibilities
Transform cutting-edge physics challenges into machine-verifiable tasks that AI systems can systematically navigate. This role entails writing production-level code, collaborating with AI researchers and engineers, and delivering operational systems that foster large-scale physics discovery.
- Design evaluation frameworks across diverse physics domains, including atomic, molecular, and optical physics, condensed matter physics, plasma physics, fluid dynamics, astrophysics, quantum information, high-energy theory, biophysics, soft matter, and statistical mechanics.
- Create verification harnesses that encode principles of physical validity, conservation laws, and experimental integrity to differentiate authentic physics insights from numerical artifacts.
- Integrate advanced physics simulations into AI environments and establish benchmarks that assess genuine physics reasoning.
- Collaborate with AI researchers to refine agent architecture and training methodologies, while developing production code that underpins extensive discovery workflows.
Qualifications
We are looking for candidates with a PhD in Physics or a related discipline, possessing in-depth knowledge in at least one significant area of physics and proficient programming skills. Ideal candidates should demonstrate a history of addressing complex, unresolved problems and excel in dynamic research settings.
Areas of Expertise:
- Profound knowledge in atomic, molecular, and optical physics, condensed matter physics, plasma physics, fluid dynamics, astrophysics, quantum information, high-energy theory, biophysics, soft matter, statistical mechanics, or equivalent physics disciplines.
- Solid understanding of physical validity, conservation laws, and experimental limitations.
Programming and Computational Skills:
- Proficient in Python and C++, with experience in computational physics simulations and high-performance computing.
- Hands-on experience with simulation tools such as VASP, Quantum ESPRESSO, LAMMPS, GROMACS, OpenFOAM, COMSOL, or similar platforms.
