Materials Engineer, CALPHAD, Terafab

Job description

Job responsibilities

• Develop, assess, and refine CALPHAD thermodynamic and mobility databases for multi-component oxide and functional materials systems
• Calculate phase diagrams, phase stability maps, and property diagrams relevant to bulk and thin-film oxide processing conditions
• Model solid-state reactions, crystallization pathways, oxygen non-stoichiometry, and interfacial phase formation in oxide and functional multilayer stacks
• Couple thermodynamic predictions with kinetic models (diffusion, precipitation, phase transformation) to define process windows for deposition, anneal, and integration steps
• Collaborate with experimentalists to design validation experiments and refine database assessments against characterization data (XRD, TEM, DSC/DTA, TGA, ellipsometry, and related methods)
• Support materials selection and composition optimization for functional oxides, including dielectrics, ferroelectrics, ion conductors, transparent conductors, and barrier/passivation layers
• Integrate CALPHAD outputs with complementary computational methods (DFT, phase-field, process models) within an ICME workflow
• Communicate modeling results and materials design recommendations to cross-functional Terafab and Materials Engineering teams through reports and presentations
• Contribute to internal materials data infrastructure, documentation standards, and reusable CALPHAD workflows

Job requirements

• Degree in Materials Science, Metallurgy, Ceramics, Chemistry, or related field with a strong emphasis on computational thermodynamics / CALPHAD, or equivalent experience
• Practical experience developing or applying CALPHAD assessments for oxide, ceramic, or complex multi-component systems
• Proficiency with commercial CALPHAD software (Thermo-Calc, FactSage, Pandat, or similar) and thermodynamic database development/assessment methods
• Strong foundation in phase equilibria, oxide crystal chemistry, defect chemistry, and thermodynamics of non-stoichiometric compounds
• Demonstrated ability to connect CALPHAD predictions to experimental phase identification and process outcomes
• Programming skills in Python, MATLAB, or similar for automation of calculations, data analysis, and workflow development
• Experience with oxide thin films, functional ceramics, or semiconductor-adjacent oxide systems is preferred
• Familiarity with DFT-informed CALPHAD parameterization, mobility databases, or DICTRA/TC-PRISMA kinetic simulations is preferred
• Experience with materials informatics, high-throughput composition screening, or coupling CALPHAD to process/device models is a plus
• Ability to travel up to 20%