Computational Materials Scientist – DFT & Thermal Materials Design
台達電子工業股份有限公司 _DELTA ELECTRONICS INC. Computational Materials Scientist – DFT & Thermal Materials Design
Description
We are seeking a Computational Materials Scientist specializing in Density Functional Theory (DFT) and first-principles modeling to develop next-generation computational materials design capabilities for thermal energy applications.
This is a DFT-focused computational materials research position. The core responsibility of this role is to use first-principles calculations to understand and predict how atomic structures, chemical composition, defects, interfaces, and bonding influence material properties, thermodynamic stability, and performance.
You will develop and apply DFT and atomistic modeling methodologies to investigate metals, alloys, ceramics, composites, and heterogeneous material systems, and translate atomic-scale insights into practical materials design strategies.
Thermal storage and thermal energy recovery will be major application areas of this position. Prior experience in thermal storage materials is not required. Candidates with strong DFT expertise in alloys, electronic materials, magnetic materials, ceramics, semiconductors, energy materials, or other materials systems are highly encouraged to apply.
Experience investigating thermal properties, thermal transport, finite-temperature behavior, or thermal storage materials through first-principles or atomistic simulations will be considered a strong plus.
Key Responsibilities:
- Conduct DFT and first-principles simulations to evaluate material structures, properties, and thermodynamic stability.
- Perform computational materials design, including atomistic modeling of metals, alloys, ceramics, composites, defects, and interfaces.
- Investigate thermal, mechanical, and thermodynamic behaviors of advanced materials for energy-related applications.
- Develop automated simulation workflows and Python-based scientific computing tools in Linux/HPC environments.
- Collaborate with experimental, engineering, AI, and product development teams to support material selection, validation, and innovation.