Materials Science Expert

Employer description and requirements

Materials Science Expert

Pay: $80–$150/hour

Location: Global, fully remote

Job Type: Contractor (~15 hours per week)

Schedule: Flexible—you choose the hours and days you work, including weekends if desired

We are looking for a highly skilled Materials Science Expert to contribute to an AI training project involving computational materials science, materials modeling, scientific simulation, and Python.

The work involves creating, solving, reviewing, and validating engineering tasks related to material structures, properties, processing, performance, and failure. A representative task may require constructing a material or atomic model, configuring and running a simulation, calculating relevant properties, analyzing the resulting outputs, and determining whether the solution is computationally valid and physically meaningful.

This is a very coding heavy role. Candidates but have experience using coding agents with python in their workflow.

What You’ll Work On

Solve and validate computational materials-science and materials-engineering problems.

Create material structures, atomic configurations, compositions, and solver-ready inputs.

Model relationships between composition, structure, processing, properties, and performance.

Run atomistic, electronic-structure, molecular-dynamics, continuum, electrochemical, or related simulations.

Use Python to generate inputs, automate calculations, conduct parameter sweeps, process results, and validate outputs.

Required Qualifications

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.

Experience using coding agents and Python.

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 the hiring manager review.

Compensation Structure

Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow.

Minimum submission requirements apply.

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.

Application screening questions

What is your expected hourly rate in USD?

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

If moving forward, would you be able to review and sign the contract within 24 hours, and begin tasking within 24-48 hours of receiving your credentials?

Do you have a portfolio or any open source evidence of your work you'd like to share with us?

Do you have teaching/instructor experience? If so, what does it look like? (Not a deal breaker)

What does your experience with Python look like?

Please select the tools you have experience with: (Would highly recommend making it visible on your application)

Please describe your experience with the previously selected tools.

Other published fields (read alongside the description):

Published hourly-rate fields: {'max': 150, 'min': 80}

Source page's structured applicant-location list: Bangladesh, Hong Kong, India, Indonesia, Japan, Kazakhstan, Kyrgyzstan, Malaysia, Pakistan, Philippines, Singapore, Sri Lanka, Taiwan, Thailand, Uzbekistan, Vietnam, Austria, Belarus, Belgium, Denmark, France, Germany, Greece, Italy, Netherlands, Portugal, Russia, Spain, Switzerland, United Kingdom, Argentina, Brazil, Chile, Colombia, Mexico, Peru, Algeria, Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Tunisia, United Arab Emirates, United States, Canada, Nigeria, Kenya, South Africa, Ghana, Ethiopia