STEM Expert – Chemistry & Computational Chemistry (PhD)
New
X
Xperteez TechnologyComputational chemistry
Remote (Worldwide)Contract
Salary45 - 90 USD per year
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Job Details
- Languages
- Professional written and spoken English (C1 or higher).
- Required Skills
- Python
Requirements
- 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 listed area, such as organic synthesis, organometallic chemistry, spectroscopy, computational chemistry, cheminformatics, or materials science.
- Professional written and spoken English at C1 or higher.
- Proficiency in Python and/or industry-standard tools in the relevant subfield, such as Gaussian, ORCA, Psi4, GROMACS, LAMMPS, or RDKit.
- Strong quantitative, analytical, and scientific reasoning skills.
- Ability to document and explain technical concepts clearly in writing and verbally.
- Track record of rigorous scientific problem-solving in complex chemistry domains.
- Academic experience as a postdoc, research scientist, faculty member, or equivalent is preferred.
- Peer-reviewed publications, patents, or contributions to open-source scientific software are preferred.
- Experience with AI/ML-assisted chemistry workflows or benchmarking is preferred.
- Background in drug discovery, reaction prediction, or retrosynthesis is preferred.
Responsibilities
- Design, evaluate, and critique chemistry and computational chemistry problems, workflows, and reasoning chains for AI benchmarking.
- Provide expert 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.
- Guide the development and validation of chemistry-related AI models and tools using domain knowledge.
- Communicate scientific concepts clearly in writing and verbally to technical and non-technical collaborators.
- Document findings, methodologies, and best practices for knowledge transfer across the customer’s team.
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