Causal Labs
Member of Technical Staff — Research, Physics
San Francisco +1 · On-site · Staff · Full-time · Posted Jul 21, 2026
- Location
- San Francisco
Singapore - Experience
- Typically a PhD or equivalent research experience.
- Education
- Typically a PhD or equivalent research experience.
About the job
Guide research on a Large Physics foundation Model by applying physical principles, evaluating physical coherence, and assessing generalization across domains.
What you'll do
- Assess model consistency with conservation laws and physical constraints, including the effects of physics-informed inductive biases.
- Develop evaluations of physical coherence and investigate how the model generalizes or breaks down across domains.
- Advise on modeled systems and numerical treatment, collaborating with model, evaluation, and interpretability teams.
What they ask for
- Deep expertise in physics, such as fluid dynamics, thermodynamics, computational physics, or a closely related field.
- Familiarity with numerical simulation of physical systems and its trade-offs.
- Ability to collaborate with ML researchers and translate physical principles into technical requirements.
- A rigorous, evidence-driven approach to evaluating model quality.
Tools
Large Physics foundation Model (LPM), CFD
AI focus
Research on a physics foundation model intended to predict and control physical systems, starting with weather; the role applies physical principles, develops evaluations, and studies cross-domain generalization.
Model-written summary · the original posting is authoritative