High-Throughput DFT Workflows for Semiconductor Properties

National Institute of Standards and Technology; Gaithersburg (MD); On-site; USD 82,000 - 87,000; Full time

Job summary

NIST's Materials Measurement Laboratory seeks an associate researcher to develop a high-throughput DFT workflow for predicting semiconductor material properties. You will build multi-scale infrastructure, run calculations with VASP/Abinit/QuantumATK, and apply Scikit-Learn for surrogate modeling. Results are presented to internal stakeholders and project teams in quarterly meetings.

The appointment is for 1 year with renewal options; relocation expenses are not provided. U.S.

Qualifications

• PhD in Materials Science and Engineering or related field.
• Experience with first-principles codes (VASP/Abinit/QuantumATK).
• Experience with ML surrogate modeling (Scikit-Learn).
• Excellent written and oral communication skills.

Responsibilities

• Develop high-throughput DFT workflows for semiconductor properties.
• Calculate properties: bandgaps, alignments, transport properties, defects.
• Present results to internal stakeholders; engage with external collaborators as needed.

Skills

PhD in Materials Science and Eng

DFT workflow design

ML surrogate modeling (Scikit-Learn)

Communication skills

Education

PhD in Materials Science and Engineering

Tools

VASP

Abinit

QuantumATK

Scikit-Learn

Job description

NIST's Materials Measurement Laboratory seeks an associate researcher to develop a high-throughput DFT workflow for predicting semiconductor material properties. You will build multi-scale infrastructure, run calculations with VASP/Abinit/QuantumATK, and apply Scikit-Learn for surrogate modeling. Results are presented to internal stakeholders and project teams in quarterly meetings.

The appointment is for 1 year with renewal options; relocation expenses are not provided. U.S.