Materials Science Expert

• An MS or PhD in Materials Science and Engineering, Metallurgy, or a closely related discipline; or
• An MS or PhD in Mechanical Engineering or Chemical Engineering with a substantial materials specialization.
• Strong understanding of materials behavior and relevant structure-property relationships.
• Experience with computational materials modeling, simulation, characterization, or materials-focused engineering analysis.
• Practical proficiency with Python.
• Experience with at least one engineering or scientific tool that can be operated through a CLI, scripting interface, configuration files, or programmatic API.
• Ability to understand and justify modeling assumptions, parameters, approximations, and convergence criteria.
• Ability to distinguish computational failures from genuine physical behavior.
• Ability to explain complex scientific reasoning and technical limitations clearly.

Relevant tools may include LAMMPS, ASE, pymatgen, Quantum ESPRESSO, FEniCSx, CalculiX, Elmer, PyBaMM, or similar programmatic materials and simulation software. Experience with an equivalent CLI-accessible tool is acceptable.

Relevant Python tools may include NumPy, SciPy, pandas, Matplotlib, Jupyter, atomistic modeling packages, materials informatics libraries, or domain-specific scientific tools. No single library is mandatory.

Experience may come from academic research, national laboratories, industry R&D, computational engineering, or other demonstrated materials work.

Process

• Apply to the role and complete the screening questions.
• Complete an AI interview of approximately 30 minutes.
• Complete a technical assessment, if required.
• Complete the hiring manager review.

Start Timeline & Availability

• We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

Originally posted on Himalayas