Postdoc: Data-Driven Materials & Manufacturing

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 70,000 - 110,000; Full time

Benefits offered by this job

Medical insurance

Dental and vision

401(k) matching

Tuition assistance

Job summary

Los Alamos National Laboratory in Los Alamos, NM invites applications for a Postdoctoral Research Associate focused on data analysis within the Chemical Diagnostics and Engineering group. The role emphasizes developing and optimizing manufacturing processes for advanced materials, working with a multidisciplinary team on materials design and fabrication methods for engineering applications.

The position requires a PhD in a related field within five years and expertise in modeling, data analysis,

Qualifications

• Ph.D. in material science, material physics, chemical engineering or a related field soon to be completed or completed within the last five years.
• Strong background in modeling solid-state materials using classical MD to model and predict material behavior and failure.
• Strong background in Density Functional Theory (DFT) to model and predict properties of solid-state materials.

Responsibilities

• Apply advanced data analysis techniques to real-world materials science and manufacturing challenges.
• Collaborate with a multidisciplinary team to design and develop materials and their fabrication methods for engineering applications.

Skills

Data analysis

Machine learning

Python

Mathematical modeling

Education

PhD in material science or related field

Tools

Python

MATLAB

VASP

DFT

MD

CrystalMaker

Job description

Los Alamos National Laboratory in Los Alamos, NM invites applications for a Postdoctoral Research Associate focused on data analysis within the Chemical Diagnostics and Engineering group. The role emphasizes developing and optimizing manufacturing processes for advanced materials, working with a multidisciplinary team on materials design and fabrication methods for engineering applications.

The position requires a PhD in a related field within five years and expertise in modeling, data analysis,