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.
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