Inorganic Chemistry & Synthesis Expert
Listing checked October 11, 2026 · pay as published by Mercor
Overview
Mercor hires PhD-level inorganic and materials chemists to support advanced AI research. You will review scientific claims, synthesis routes, and experimental results for accuracy, then build reference answers that teach models to reason through chemistry. The work spans solid-state chemistry, materials synthesis, and characterization methods such as XRD, XPS, and electron microscopy. A strong background in crystallography, thermodynamics, and reaction kinetics matters more than generic AI experience. Hours start at 10 per week and can reach 40.
What You'll Do7
- 1Evaluate hard problems in solid-state chemistry, inorganic chemistry, and materials synthesis.
- 2Review AI-generated explanations, synthesis pathways, and experimental methods, then flag errors or gaps.
- 3Assess reaction mechanisms, precursor choices, reaction conditions, phase formation, and material stability.
- 4Write rigorous reference answers, technical evaluations, and reasoning frameworks for scientific topics.
- 5Spot mistakes in chemical reasoning, proposed synthetic routes, and interpretations of experimental data.
- 6Apply characterization tools such as XRD, XPS, SEM, and Raman spectroscopy.
- 7Partner with research teams to raise the scientific accuracy and reliability of advanced AI models.
Requirements10
- 1PhD in inorganic chemistry, materials chemistry, solid-state chemistry, materials science, or a field tied to those areas. MSc candidates with deep research records can qualify.
- 2Hands-on work with inorganic synthesis, solid-state reactions, solution-phase synthesis, hydrothermal methods, or solvothermal methods.
- 3Solid grasp of crystallography, phase diagrams, chemical bonding, thermodynamics, and reaction kinetics.
- 4Ability to interpret experimental characterization data and judge scientific literature.
- 5Clear scientific writing, analytical reasoning, and communication.
- 6Capacity to evaluate complex scientific problems on your own.
- 7Research on catalysts, metal oxides, ceramics, semiconductors, coordination compounds, or functional inorganic materials.
- 8Peer-reviewed publications or patents in inorganic chemistry or materials synthesis.
- 9Experience linking experimental chemistry to computational materials science.
- 10Prior work evaluating scientific datasets, technical benchmarks, or AI-generated research outputs.
Who Should Apply
An ideal candidate holds a PhD in inorganic chemistry, materials chemistry, solid-state chemistry, or materials science and has run synthesis campaigns from precursor selection through phase identification. You should read characterization data from XRD, XPS, SEM, and Raman spectroscopy and explain what each result means for a proposed mechanism. This role fits researchers who enjoy writing technical evaluations and catching faulty reasoning in AI outputs. A candidate without bench experience in inorganic synthesis will struggle, because the work requires judgment about real reaction conditions, not just literature summaries. Applicants also lose fit when they list publications but cannot describe specific synthesis steps, characterization choices, or how they would validate an AI-generated route.
Salary Insight
The role pays $84.00 per hour. That rate sits above many general AI data roles and matches senior PhD-level expert work in chemistry and materials science. Mercor asks for a minimum of 10 hours per week and allows up to 40, so total earnings depend on your available schedule.
Pay and demand for AI Training roles
AggregatedTypical pay
$70/hour
This role
$84/hr
Most AI Training roles pay $37–$95 per hour. This role's pay falls inside that range.
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Compensation
$84/hr
Required Skills
Application Tip
Open your application with a short synthesis case study. Name the materials you made, the methods you used, such as hydrothermal or solvothermal routes, and the characterization tools you relied on, including XRD, XPS, and Raman spectroscopy. Add one example where you judged an incorrect scientific explanation or synthetic pathway, because Mercor screens for review skill as much as laboratory background. Quantify your output with publication count, years at the bench, or hours spent evaluating technical datasets.
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