Computational Materials Research Engineer

Short Summary

Computational Materials Research Engineer with Western Digital. We are looking for a motivated individual to join Western Digital Research, a world-class research laboratory in San Jose, California with ~80 employees. Research activities in the lab focus on information storage, sensors, spintronics, superconducting devices, and AI memory/compute architectures. The materials team engages in experimental and computational…

Key Details

• Position / opportunity: Computational Materials Research Engineer
• Organization: Western Digital
• Country / coverage: United States
• Location: San Jose, CA, United States
• Work arrangement: On-site
• Opportunity type: Jobs
• Sector: Health
• Compensation: Not specified
• Duration: Not specified
• Start date: 2026-08-26
• Application deadline: Not specified

Description

We are looking for a motivated individual to join Western Digital Research, a world-class research laboratory in San Jose, California with ~80 employees. Research activities in the lab focus on information storage, sensors, spintronics, superconducting devices, and AI memory/compute architectures. The materials team engages in experimental and computational research activity with the mission to develop novel materials for emerging technologies. The team is well-equipped with thin film deposition tools, related characterization methods and support staff, located in a fully functional cleanroom with the capability to fabricate a wide array of nanoscale devices using novel materials. Essential Duties and Responsibilities: Conducting and developing new capabilities in computational simulations of materials, interfaces and devices, including all forms of transport phenomena (e.g., thermal, electronic, spin). Work on AI assisted materials exploration and discovery with a focus on evaluating key material properties and interactions for device design. For this work, AI and machine learning techniques will be used to accelerate atomistic material simulations and to conduct rapid assessments of large material candidate pools. Work closely with experimental teams to guide material exploration and assist in interpreting experimental results. The work environment rewards innovative thinking and a highly collaborative attitude. 3+ years or higher experience in computational materials science with strong background in solid-state physics and devices. PhD in Physics, Materials Science, Electrical Engineering, Chemistry, or Chemical Engineering. Expert knowledge of atomistic simulation techniques such as density functional theory and classical molecular dynamics. Experience with ab-initio codes including QuantumATK, VASP, Quantum Espresso, Questaal, and KKR-CPA. Familiarity with PAOFLOW or WANNIER90. Experience with molecular dynamics codes such as LAMMPS. Experience using machine learned interatomic potentials for large scale atomistic simulations is a plus. Experience with broad computational material searches and machine learning techniques relevant for atomistic simulations. This includes, but is not limited to, machine learning neural networks for expedited prediction of material properties based on crystal structure features and DFT training sets. Experience in magnetism and magnetic materials, spin-orbit interactions, spin Hall materials, ordered and disordered materials, electronic, spin and thermal transport. Knowledge of chemical interactions at material interfaces and surfaces would also be an asset for a strong candidate. Experience predicting transport properties (e.g. spin Hall conductivity, anomalous Hall conductivity) from first principles using either non-equilibrium Green’s function techniques (NEGF) or Kubo-Greenwood formalism would also be a plus. Competent programming skills and familiarity with high performance computing environments. Experience coding in Python and working with material simulation environments like ASE would be highly beneficial. Excellent written communication and organizational skills. High attention to detail. Strong work ethic. WD is committed to providing equal opportunities to all applicants and employees and will not discriminate against any applicant or employee based on their race, color, ancestry, religion (including religious dress and grooming standards), sex (including pregnancy, childbirth or related medical conditions, breastfeeding or related medical conditions), gender (including a person’s gender identity, gender expression, and gender-related appearance and behavior, whether or not stereotypically associated with the person’s assigned sex at birth), age, national origin, sexual orientation, medical condition, marital status (including domestic partnership status), physical disability, mental disability, medical condition, genetic information, protected medical and family care leave, Civil Air Patrol status, military and veteran status, or other legally protected characteristics. We also prohibit harassment of any individual on any of the characteristics listed above. Our…

Responsibilities

• We are looking for a motivated individual to join Western Digital Research, a world-class research laboratory in San Jose, California with ~80 employees.
• Research activities in the lab focus on information storage, sensors, spintronics, superconducting devices, and AI memory/compute architectures.
• The materials team engages in experimental and computational research activity with the mission to develop novel materials for emerging technologies.
• The team is well-equipped with thin film deposition tools, related characterization methods and support staff, located in a fully functional cleanroom with the capability to fabricate a wide array of nanoscale devices using novel materials.
• Essential Duties and Responsibilities: Conducting and developing new capabilities in computational simulations of materials, interfaces and devices, including all forms of transport phenomena (e.g., thermal, electronic, spin).
• Work on AI assisted materials exploration and discovery with a focus on evaluating key material properties and interactions for device design.

Requirements / Eligibility

• magnetism and magnetic materials, spin-orbit interactions, spin Hall materials, ordered and disordered materials, electronic, spin and thermal transport.
• Knowledge of chemical interactions at material interfaces and surfaces would also be an asset for a strong candidate.
• Experience predicting transport properties (e.g.
• spin Hall conductivity, anomalous Hall conductivity) from first principles using either non-equilibrium Green’s function techniques (NEGF) or Kubo-Greenwood formalism would also be a plus.

How To Apply

Use the Apply now button and follow the instructions on the application page.