Senior Computational Materials Scientist

Commonwealth Fusion Systems•Devens, MA

1d•Hybrid

About The Position

Commonwealth Fusion Systems (CFS) is developing commercially viable fusion power plants and is seeking a Senior Computational Materials Scientist for its Materials and Processing Department. The department supports design engineering, supply chain, and manufacturing by selecting and defining materials and processing routes, validating and measuring materials and their properties, and conducting research and development. Its work supports SPARC, under construction in Devens, Massachusetts, and the design of the ARC fusion power plant. These projects involve materials challenges such as neutron flux, high heat loads, molten salt coolant systems, complex component geometries, high magnetic fields, and high mechanical loading at cryogenic temperatures. The role focuses on computational materials science, process-structure-properties relationships, physics-informed modeling, and materials in extreme environments. The scientist will use computational simulation, synthetic data generation, and first-principles modeling to support materials development. They will work with engineers and subject matter experts to identify sensitive parameters and prioritize experiments that most effectively reduce uncertainty. The position is full-time and includes salary, equity, and benefits.

Requirements

Degree or background in Materials Science and Engineering, Applied Physics, Applied Mathematics, Physical Chemistry, Computer Science, or a related field.
At least 7 years of experience in experimental or computational materials science.
Experience using computational materials science and integrated computational materials engineering (ICME) tools to address scientific or engineering questions across length scales.
Experience implementing and/or authoring code to calculate and analyze material properties and microstructures.
Experience with predictive models for material properties and microstructure evolution in extreme environments.
Ability to validate models using experimental data or bounds based on physical mechanisms.
Understanding of process-structure-properties-performance principles and mechanisms responsible for property changes in extreme environments.
Understanding of models enabling materials simulation across length scales, including atomistic methods, molecular dynamics, density functional theory, Monte Carlo, phase field, crystal plasticity, dislocation dynamics, computational thermodynamics, and finite element methods.
Knowledge of scientific computing, numerical algorithms, FEM, FD, FVM, BEM, eigenvalue, linear and PDE solvers, convex optimization, computational geometry, and advanced statistical methods.
High-performance computing experience, including distributed processing, message-passing interfaces, and GPU acceleration.
Understanding of sensitivity to uncertainty in calculation and model inputs and outputs.
Demonstrated ability to work effectively cross-functionally.
Strong organizational skills, including prioritizing multiple concurrent projects.
Ability to break complex problems into smaller deliverables that add value.
Ability to type and sit for extended periods.
Commitment to safety in environments with potential industrial hazards, including heat, cold, noise, fumes, strong magnets, lead, high voltage, and cryogenics.
Willingness to travel or work nights, weekends, or on-call occasionally; travel is less than 10%.
Must comply with U.S. export control laws concerning controlled or protected technologies or information; any employment offer is contingent on this compliance.

Nice To Haves

Experience presenting complex quantitative data in a simple, intuitive format and communicating findings clearly and concisely.
Experience making and justifying decisions in fast-paced engineering settings.
Written and verbal communication skills with technical teams.
Ability to take under-defined problems and drive them to completion.
Experience operating in a flexible, service-oriented engineering domain team.

Responsibilities

Use and develop computational toolsets, workflows, and methods to predict material properties in extreme environments, with uncertainty bounds informed by physical mechanisms.
Identify chemical and microstructural features that affect material performance in extreme environments, and quantify relationships for engineering optimization.
Inform the design of experiments for materials exposed to combinations of corrosion, stress, irradiation, magnetic fields, electric fields, and high temperatures.
Develop, with design and analysis engineers, methodologies for material design curves that determine statistically significant minimum properties for applications such as low- and high-cycle fatigue, dielectric breakdown, and radiation effects.
Identify knowledge and experimental capability gaps that can be addressed through simulation or model building.
Assist in benchmarking and creating metrics for material-property variability and variability sources across manufacturing, fabrication, assembly, and processing.
Collaborate with Materials and Processing engineers to develop workflows for capturing, storing, visualizing, and analyzing materials-domain data.
Support the writing of material standard specifications.
Stay current with evolving technology and modeling techniques.
Collaborate with engineers and subject matter experts to identify sensitive parameters and prioritize experimental work to reduce uncertainty.