STEM Expert – Chemistry & Computational Chemistry (PhD)

micro1

United States

Remote

USD 90,000 - 150,000

Full time

32 hours ago
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Qualifications

  • PhD in chemistry, computational chemistry, chemical biology, materials science, or a closely related field.
  • Hands-on research lab experience or extensive simulation-heavy research.
  • Deep expertise in at least one listed area.
  • Professional written and spoken English (C1 or higher).
  • Proficiency in Python and common tools (Gaussian/ORCA/Psi4/GROMACS/LAMMPS/RDKit).
  • Excellent quantitative, analytical, and scientific reasoning skills.
  • Outstanding written and verbal communication abilities.

Responsibilities

  • Design, evaluate, and critique chemistry and computational chemistry problems and workflows for AI benchmarking.
  • Provide expert insights on reaction mechanisms, synthesis planning, spectroscopy, and simulations.
  • Assess and optimize experimental protocols and software configurations for accuracy and reproducibility.
  • Analyze chemical, spectroscopic, and simulation data and provide actionable recommendations.
  • Guide development and validation of chemistry-related AI models and tools.
  • Communicate complex concepts clearly to technical and non-technical collaborators.
  • Document findings and methodologies to enable knowledge transfer.

Skills

Python
Scientific reasoning
Clear communication

Education

PhD in chemistry/computational chemistry

Tools

Gaussian
ORCA
Psi4
GROMACS
LAMMPS
RDKit

Job description

Role Title: STEM Expert - Chemistry & Computational Chemistry (PhD) Role Type: Contractor Location: Remote (Worldwide)

Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Key Responsibilities:
  • Design, evaluate, and critique chemistry and computational chemistry problems, workflows, and reasoning chains to support AI benchmarking initiatives.
  • Provide expert-level insights on reaction mechanisms, synthesis planning, spectroscopy analysis, molecular simulations, and electronic structure methods.
  • Assess and optimize experimental protocols, simulation parameters, and software configurations for accuracy and reproducibility.
  • Analyze chemical, spectroscopic, and simulation data and provide actionable recommendations.
  • Leverage domain knowledge to guide the development and validation of chemistry-related AI models and tools.
  • Communicate complex scientific concepts clearly, both in writing and verbally, to technical and non-technical collaborators.
  • Document findings, methodologies, and best practices to ensure knowledge transfer across the customer’s team.
Areas of Expertise (we welcome applicants from any of the following):
  • Organic synthesis & reaction mechanisms
  • Inorganic & organometallic chemistry
  • Physical & theoretical chemistry
  • Analytical chemistry & spectroscopy
  • Computational chemistry & molecular dynamics
  • Cheminformatics & drug discovery
  • Materials science & polymer chemistry
Required Skills and Qualifications:
  • PhD in chemistry, computational chemistry, chemical biology, materials science, or a closely related field.
  • Hands-on research lab experience , including wet lab experience for experimental subfields, or extensive simulation-heavy research for computational subfields.
  • Deep expertise in at least one of the areas listed above.
  • Professional written and spoken English (C1 or higher).
  • Proficiency in Python and/or industry-standard tools in your subfield (e.g., Gaussian, ORCA, Psi4, GROMACS, LAMMPS, RDKit).
  • Excellent quantitative, analytical, and scientific reasoning skills.
  • Outstanding written and verbal communication abilities, with the ability to clearly document and explain technical concepts.
  • Track record of rigorous scientific problem-solving in complex chemistry domains.
Preferred Qualifications:
  • Academic experience (postdoc, research scientist, faculty, or equivalent), strongly preferred.
  • Peer-reviewed publications, patents, or contributions to open-source scientific software.
  • Experience with AI/ML-assisted chemistry workflows or benchmarking.
  • Background in drug discovery, reaction prediction, or retrosynthesis.
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