CALPHAD & AI-Driven Alloy Design Scientist

Discovery 2 Scale; Santa Fe (NM); On-site; USD 110,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Health benefits

401(k) with company match

Job summary

Discovery 2 Scale is building the Autonomous Foundry for Advanced Materials—an end-to-end platform connecting materials design, autonomous experimentation, qualification, and scale-up to deliver production-ready materials faster and with less risk.

We seek a highly skilled computational materials scientist with CALPHAD and Thermo-Calc experience to help build the thermodynamic intelligence behind our platform, and to develop workflows, models, and pipelines that integrate with AI/ML and

Qualifications

• MS/PhD in Materials Science, Metallurgy or related field.
• Hands-on Thermo-Calc and CALPHAD experience.
• Experience modeling multicomponent metallic alloy systems.
• Experience with equilibrium phase and Scheil solidification calculations.
• Strong understanding of physical metallurgy, thermodynamics, solidification, and phase transformations.
• Experience with scientific programming or workflow automation using Python.

Responsibilities

• Develop CALPHAD and Thermo-Calc workflows for alloy design and high-throughput screening.
• Model phase stability, solidification, segregation, and phase transformations.
• Perform Scheil and kinetic simulations to evaluate manufacturability and processing windows.
• Develop models for weldability, heat-affected-zone behavior, and thick-section producibility.
• Build automated Python and Thermo-Calc pipelines for large composition and processing spaces.
• Integrate thermodynamic predictions with AI/ML models and experimental data to guide alloy design.

Skills

CALPHAD

Thermo-Calc

Python

Multicomponent alloys

Numerical modeling

Education

MS or PhD in Materials Science/Metallurgy/Computational Materials Science

Tools

Thermo-Calc

TC-Python

DICTRA

TC-PRISMA

Job description

Discovery 2 Scale is building the Autonomous Foundry for Advanced Materials—an end-to-end platform connecting materials design, autonomous experimentation, qualification, and scale-up to deliver production-ready materials faster and with less risk.

We seek a highly skilled computational materials scientist with CALPHAD and Thermo-Calc experience to help build the thermodynamic intelligence behind our platform, and to develop workflows, models, and pipelines that integrate with AI/ML and