AI Chemistry Research Specialist (PhD) – Benchmarking

Gramian Consulting Group; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Gramian Consultancy seeks a PhD-level Chemistry and Computational Research Specialist to lead design, evaluation, and validation of AI benchmarking workflows in chemistry. You will assess reaction mechanisms, spectroscopy, molecular modeling, and computational workflows while ensuring reproducibility and rigorous scientific standards.

The role emphasizes strong quantitative reasoning, clear communication of findings, and the ability to guide AI model development with deep chemistry expertise.

Qualifications

• PhD in Chemistry or closely related field required.
• Hands-on research experience in a lab or extensive simulation-based research experience.
• Deep expertise in at least one listed chemistry or computational area.
• Professional written and spoken English at C1 level or higher.
• Proficiency in Python and/or relevant scientific software.

Responsibilities

• Design, evaluate, and critique chemistry problems, workflows, and reasoning chains for AI benchmarking.
• Assess chemical reasoning involving mechanisms, synthesis planning, retrosynthesis, spectroscopy, and molecular modeling.
• Evaluate experimental protocols, simulation parameters, and software configurations for accuracy and reproducibility.
• Analyze chemical, spectroscopic, experimental, and simulation data to identify errors and opportunities for improvement.
• Guide development and validation of chemistry-focused AI models and tools.
• Review AI-generated outputs for correctness and methodological soundness.

Skills

Python

Analytical reasoning

Scientific writing

English proficiency

Education

PhD in Chemistry or related field

Tools

Gaussian

ORCA

Psi4

GROMACS

LAMMPS

RDKit

Job description

Gramian Consultancy seeks a PhD-level Chemistry and Computational Research Specialist to lead design, evaluation, and validation of AI benchmarking workflows in chemistry. You will assess reaction mechanisms, spectroscopy, molecular modeling, and computational workflows while ensuring reproducibility and rigorous scientific standards.

The role emphasizes strong quantitative reasoning, clear communication of findings, and the ability to guide AI model development with deep chemistry expertise.