About the job
About Periodic Labs
Periodic Labs is an innovative AI and physical sciences laboratory dedicated to constructing advanced models that facilitate groundbreaking scientific discoveries. With robust funding and rapid growth, we empower our team members to take ownership, identify challenges, and solve problems in an environment free from limitations and bureaucracy. Our passion for learning new tools and sciences drives our mission forward.
About the Role
We are excited to invite a seasoned Multiphysics Simulation Scientist / Engineer to join our elite team of scientists and engineers. In this pivotal role, you will be instrumental in advancing our physical R&D initiatives within a pioneering lab where AI and automation revolutionize the pace and scale of discoveries.
As a Multiphysics Simulation Scientist, you will develop, execute, and integrate high-fidelity physical simulations of our experimental systems, effectively linking materials processes with thermal and mechanical environments as well as electrical and magnetic behaviors to our AI-driven R&D pipelines.
Key Responsibilities
Create and implement multiphysics models for various processes, including thermal, mechanical, electromagnetic, plasma, fluid flow, and chemical reaction phenomena.
Connect simulations with orchestration systems and data infrastructure to enable real-time digital twins and AI feedback loops.
Generate diverse simulated datasets for machine learning training and reinforcement learning environments.
Collaborate with teams in computational science, AI, automation, processes, and facilities to enhance R&D workflows.
Qualifications
PhD or MS in Mechanical, Chemical, Materials, Aerospace Engineering, or closely related fields.
5+ years of practical experience with multiphysics modeling tools (e.g., COMSOL, ANSYS, or other finite-element / finite-volume solvers) to address a broad range of real-world challenges across electronics, automotive, aerospace, or chemical manufacturing sectors.
In-depth knowledge of coupled physical processes, such as heat transfer, stress analysis, diffusion phenomena, plasma/fluid dynamics, and electromagnetism.
Proficiency in Python programming.
Bonus Qualifications
Experience in modeling thin-film deposition and associated chemical reactions.
Familiarity with machine learning methodologies relevant to multiphysics modeling.
Ability to collaborate effectively across disciplines with engineers, scientists, and machine learning specialists.