Senior Computational Materials Scientist_CTO Office (Taipei)

We are seeking an exceptional Computational Materials Scientist to pioneer the AI for Science R&D and discovery of next-generation materials for Delta’s products.
As part of CTO Office, you will help build the computational foundation that connects fundamental materials physics with long-term industrial innovation. Using density functional theory (DFT) and physics-based materials modeling, you will uncover how atomic structure, chemistry and magnetic ordering govern critical material properties and transform these insights into actionable directions for experimental development.
The initial focus will be soft magnetic materials, particularly spinel ferrites and related magnetic compounds. You will lead first-principles investigations, establish validated computational methodologies and evaluate candidate materials proposed through scientific insight, database exploration and AI-assisted materials discovery.
Experience with Machine Learning Interatomic Potentials or Force Fields (MLIPs/MLFFs) is highly valued, but not mandatory.

Key Responsibilities
•Perform spin-polarized DFT calculations to evaluate magnetic ordering, thermodynamic stability, electronic structure and intrinsic magnetic properties.
•Develop and validate computational methods for key properties, including Bs, magnetic moments, K1, electronic structure and resistivity-related descriptors.
•Analyze the effects of composition, crystal structure and cation distribution on magnetic performance.
•Screen and prioritize candidate materials for experimental synthesis and validation.
•Collaborate with AI, magnetic-material and experimental teams to translate industrial requirements into executable computational studies.
•Build reusable calculation methods, research knowledge and internal computational assets.

Required Qualifications
•Ph.D. or Master degree in Materials Science, Physics, Chemistry, Chemical Engineering or a related field
•Strong hands-on experience in DFT calculations for inorganic or solid-state materials.
•Experience with Quantum ESPRESSO, VASP, CASTEP, ABINIT or an equivalent first-principles package.
•Knowledge of spin-polarized/orbital-coupling calculations, crystal structures and electronic-structure analysis.
•Proficiency in Python, Linux and HPC environments.
•Ability to independently define computational studies, analyze results and communicate scientific insights.