Remote | Computational Materials Scientist — Up to $80/hour

We are sharing a specialised part-time consulting opportunity for experienced computational materials scientists with deep expertise in atomistic modelling, surface and interface science, first-principles simulation, and computational catalysis.

This long-term role supports an advanced AI research initiative focused on materials science and the physical sciences. Selected professionals will apply expert-level knowledge of atomistic simulation, electronic structure, surfaces, adsorption, and reaction energetics to develop scientific training data, evaluate AI-generated reasoning, and create technically rigorous problems and reference solutions.

Key Responsibilities

Atomistic & Materials Modelling

• Apply first-principles and molecular simulation methods to complex materials-science problems
• Work with approaches including DFT, ab initio molecular dynamics, classical molecular dynamics, and Monte Carlo methods
• Develop technically accurate simulation setups and reference analyses
• Evaluate assumptions, boundary conditions, convergence choices, and modelling methodology
• Apply professional scientific judgment to realistic computational materials scenarios

Surface, Interface & Reaction Modelling

• Develop and evaluate models involving surfaces, interfaces, adsorption, and reaction phenomena
• Work with slab models, surface reconstructions, and adsorption configurations
• Analyse reaction pathways, transition states, and activation energetics
• Apply NEB and related methods where appropriate
• Evaluate microkinetic and surface-reaction models within relevant scientific contexts

Scientific Evaluation & Problem Development

• Design and solve challenging expert-level problems in atomistic and surface modelling
• Review AI-generated scientific reasoning for technical accuracy and completeness
• Identify errors involving simulation methodology, energetics, structure, or physical interpretation
• Rate and rank model outputs against defined scientific criteria
• Provide concise written reasoning supporting evaluation decisions

Technical Data Development

• Structure simulation methods, parameters, workflows, and results into organised model-ready data
• Develop high-quality reference material for scientific training and evaluation
• Ensure technical information is internally consistent and reproducible
• Translate specialised computational knowledge into clear written explanations
• Deliver reliable work according to defined project timelines and quality standards

Ideal Profile

Strong candidates may have:

• Hands-on expertise in atomistic modelling using first-principles or molecular simulation methods
• Experience with DFT, ab initio molecular dynamics, classical MD, Monte Carlo, or related techniques
• Substantial experience modelling surfaces, interfaces, adsorption, or chemical reactions
• Familiarity with slab models, surface reconstructions, transition-state analysis, NEB, or microkinetics
• Experience with semiconductor-relevant materials or computational heterogeneous catalysis
• Strong scientific reasoning and quantitative problem-solving skills
• Ability to explain complex computational methodology clearly and concisely
• Availability for at least 10 hours per week
• Current residence in the United States

Educational Background

• A PhD in materials science, chemistry, physics, chemical engineering, or a closely related field is expected
• Several years of research experience beyond the PhD may strengthen an application
• Strong research experience in computational materials science, surface science, or catalysis is particularly valuable

Nice to Have

• Experience with VASP
• Familiarity with Quantum ESPRESSO, CP2K, or GPAW
• Experience with LAMMPS
• Proficiency with ASE, pymatgen, or related computational materials tools
• Background in semiconductor materials modelling
• Experience in computational heterogeneous catalysis
• Expertise in reaction-energy calculations and transition-state modelling
• Experience connecting atomistic simulations with experimental or materials-characterisation results
• Prior experience with scientific AI evaluation, annotation, or structured technical review

Why This Opportunity

• Apply advanced computational materials expertise to frontier AI research
• Work with realistic atomistic, surface, interface, and reaction-modelling problems
• Help improve scientific reasoning across materials science and physical-science applications
• Create and evaluate technically demanding expert-level content
• Participate in a long-term remote engagement with flexible weekly hours
• Contribute between approximately 10 and 40 hours per week depending on availability and project needs

Contract Details

• Independent contractor role
• Fully remote within the United States
• Long-term, ongoing engagement
• Minimum commitment of approximately 10 hours per week
• Potential workload of up to approximately 40 hours per week
• Compensation of up to $80 per hour depending on expertise and project scope
• Work may include atomistic modelling, scientific problem development, AI output evaluation, technical data structuring, and computational materials analysis
• Weekly payments via Stripe or Wise
• Projects may be extended, shortened, or adjusted depending on scope and performance
• Work will not involve access to confidential or proprietary information from any employer, client, or institution

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy.