Computational Materials Scientist

This is a fully remote position, open to applicants in New York.

📋 Description

• Utilize first-principles and molecular simulation techniques to tackle intricate materials-science challenges.

• Create technically precise simulation setups and reference analyses.

• Assess assumptions, boundary conditions, convergence choices, and modeling methodologies.

• Design and evaluate models that encompass surfaces, interfaces, adsorption, and reaction phenomena.

• Analyze reaction pathways, transition states, and activation energetics.

• Develop and resolve advanced issues in atomistic and surface modeling.

• Review AI-generated scientific reasoning for technical precision and completeness.

• Identify inaccuracies in simulation methodology, energetics, structure, or physical interpretation.

• Evaluate and rank model outputs against established scientific criteria.

• Provide succinct written justifications for evaluation decisions.

• Organize simulation methods, parameters, workflows, and results into structured, model-ready data.

• Create reference materials for scientific training and evaluation.

• Translate specialized computational knowledge into clear written explanations.

• Deliver dependable work in accordance with specified project timelines and quality standards.

⛳️ Requirements

• Proven computational materials scientist with extensive expertise in atomistic modeling, surface and interface science, first-principles simulation, and computational catalysis.

• Practical experience in atomistic modeling utilizing first-principles or molecular simulation methods.

• Familiarity with DFT, ab initio molecular dynamics, classical molecular dynamics, Monte Carlo, or similar techniques.

• Significant experience in modeling surfaces, interfaces, adsorption, or chemical reactions.

• Knowledge of slab models, surface reconstructions, transition-state analysis, NEB, or microkinetics.

• Background in semiconductor-relevant materials or computational heterogeneous catalysis.

• Strong scientific reasoning and quantitative problem-solving abilities.

• Capable of explaining complex computational methodologies in a clear and concise manner.

• Availability for a minimum of 10 hours per week.

• Current residence in the United States.

• A PhD in materials science, chemistry, physics, chemical engineering, or a closely related discipline is anticipated.

• Solid research experience in computational materials science, surface science, or catalysis.

• Proficient in VASP.

• Familiarity with Quantum ESPRESSO, CP2K, or GPAW.

• Experience with LAMMPS.

• Proficiency with ASE, pymatgen, or similar computational materials tools.

• Background in semiconductor materials modeling.

• Experience in computational heterogeneous catalysis.

• Expertise in reaction-energy calculations and transition-state modeling.

• Experience linking atomistic simulations with experimental or materials-characterization outcomes.

• Prior involvement in scientific AI evaluation, annotation, or structured technical review.

🏝️ Benefits

• Flexible weekly working hours.

• Long-term, continuous engagement.

• Weekly payments through Stripe or Wise.

• Opportunity for remote consulting.

• Potential workload of up to approximately 40 hours per week, depending on availability and project requirements.