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. 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