Atomic-Scale Quantum Materials Scientist

Pronoia; Torrance (CA); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Health insurance

Unlimited PTO

Professional development stipend

Relocation assistance

Job summary

Pronoia Energy in Torrance, CA is seeking a Computational Scientist to drive simulation-driven decision making for quantum energy storage materials. You will simulate atomic- and molecular-scale behavior, guiding experimental work and accelerating development cycles.

The role emphasizes building standards for simulation, collaborating with physicists and chemists, and translating models into actionable experimental plans in a fast-paced startup environment.

Qualifications

• PhD-level expertise in computational materials science, physics, or chemistry.
• Strong production coding in Python or C++ with experience in simulation packages.
• Experience linking simulations to experimental outcomes and decisions.
• Self-starter thriving amid ambiguity and rapid iteration.

Responsibilities

• Build and run atomic- and molecular-scale simulations of materials and candidate structures.
• Connect simulation results to experimental decisions and validate models against data.
• Establish tools, methods, and standards for simulation across the company.
• Collaborate with experimental teams to generate ground-truth data.
• Provide data-driven insight that informs each design iteration.

Skills

Python

C++

Computational materials science

Education

PhD in computational materials science, condensed-matter physics, or computational chemistry

Tools

Simulation packages

Job description

Pronoia Energy in Torrance, CA is seeking a Computational Scientist to drive simulation-driven decision making for quantum energy storage materials. You will simulate atomic- and molecular-scale behavior, guiding experimental work and accelerating development cycles.

The role emphasizes building standards for simulation, collaborating with physicists and chemists, and translating models into actionable experimental plans in a fast-paced startup environment.