Computational Materials Science Expert
You will complete tasks at the intersection of ML and materials research — including model development, simulation data analysis, and research tasks applied to real atomistic, electronic, or structural materials datasets.
Hiring companyAfterQuery Experts
About the role
This is a remote, project-based role for machine learning professionals with deep expertise in computational materials science.
This position offers exceptional pay, exposure to cutting-edge materials research problems, and a strong addition to your research portfolio.
Why Apply
- Flexible Time Commitment – Work on your schedule while tackling meaningful scientific challenges.
- Startup Exposure – Work directly with an early-stage Y Combinator-backed company, gaining hands-on experience that sets you apart.
- Exceptional Pay – Project-based pay ranges from $150–$200/hour.
- Portfolio Building – Gain experience applying ML to frontier computational materials problems.
- Professional Growth – Sharpen your skills on complex, real-world materials datasets and models.
Responsibilities
- Apply machine learning techniques to materials science problems, including property prediction, materials discovery, and structure-property relationship modeling.
- Build, train, and evaluate ML models trained on simulation data such as DFT, molecular dynamics, or Monte Carlo outputs.
- Develop predictive models using supervised and unsupervised learning approaches relevant to materials systems.
- Contribute to materials informatics workflows integrating ML with high-throughput computational pipelines.
- Document methodologies, model assumptions, and technical approaches clearly and reproducibly.
Required skills
- Demonstrated expertise in both machine learning and computational materials science (e.g., DFT, force field development, atomistic simulation, or materials informatics).
- Strong problem-solving skills and ability to work independently on technical tasks.
Preferred skills
- Background in TA'ing or teaching computational physics, chemistry, or materials science courses.
- Familiarity with materials-focused ML frameworks (e.g., CGCNN, MatGL, M3GNet, ALIGNN, or similar graph neural network approaches).
- Experience with computational materials tools and frameworks (e.g., VASP, Quantum ESPRESSO, LAMMPS, ASE, or similar).
Experience and education
- Published researcher with at least one first-author publication in a peer-reviewed journal.
- Master's or PhD in Materials Science, Computational Chemistry, Physics, Computer Science, or a related quantitative field.
Assessment requirements
Resume
Schedule details
Work is over the next 2–3 weeks, asynchronous, and assigned on a project-by-project basis, with an expected commitment of 10–20 hours per week for the projects you accept.
Time Commitment: 10 hours/week.
Start Date: ASAP.
End Date: Ongoing.
Eligibility
Work arrangement: Fully remote
Compensation details
- $150 - $200/hr.
More about the hiring companyAfterQuery Experts
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