Postdoc: ML-Driven Chemistry & Automated Discovery

Carnegie Mellon University; Pittsburgh (Allegheny County); On-site; USD 60,000 - 80,000; Full time

Job summary

The Isayev Lab at Carnegie Mellon University seeks a postdoctoral researcher to lead projects bridging computational chemistry and machine learning. Focused on developing predictive models and workflows, the successful candidate will collaborate in a dynamic lab environment.

We encourage applications from those holding a Ph.D. in related fields, with strong experience in DFT studies, machine learning, and programming. Candidates will work on advancing research in mechanistic studies and catalysis.

Qualifications

• Ph.D. in chemistry or related field required.
• Experience in computational reaction mechanisms.
• Fluency with Python and scientific computing workflows.
• Interest in machine learning and data-driven prediction.

Responsibilities

• Lead projects in computational chemistry and machine learning.
• Develop automated DFT/ML workflows.
• Collaborate with experimental groups for hypothesis testing.
• Create reusable software workflows for reaction data.

Skills

Fluency with Python

Experience with Git

Familiarity with DFT studies

Knowledge of machine learning

Education

Ph.D. in chemistry, chemical engineering, materials science, or related field

Tools

Gaussian

Q-Chem

SLURM

RDKit

Job description

The Isayev Lab at Carnegie Mellon University seeks a postdoctoral researcher to lead projects bridging computational chemistry and machine learning. Focused on developing predictive models and workflows, the successful candidate will collaborate in a dynamic lab environment.

We encourage applications from those holding a Ph.D. in related fields, with strong experience in DFT studies, machine learning, and programming. Candidates will work on advancing research in mechanistic studies and catalysis.