Postdoc: Polymer Biodegradation & Computational Modeling

University of Cincinnati; Cincinnati (OH); Hybrid; USD 60,000 - 75,000; Full time

Benefits offered by this job

Tuition remission

Comprehensive health coverage

Retirement plans (OPERS/STRS/ARP)

Vacation and sick time

11 paid holidays

Job summary

The University of Cincinnati, through the P&G Digital Accelerator@UC, invites applications for a postdoctoral researcher focused on computational modeling of polymer biodegradation and performance polymer behavior. The researcher will be employed by the University of Cincinnati and collaborate closely with P&G and UC technical teams.

Addressing high‑impact sustainability and performance challenges using applied computational modeling.

Qualifications

• Ph.D. in chemical engineering, chemistry, physics, materials science, or related field with specialization in computational chemistry or molecular modeling.
• Strong background in molecular dynamics, free energy calculations, and enhanced sampling techniques.
• Experience with at least one programming language.

Responsibilities

• Develop computational models to predict polymer biodegradation pathways, rates, and intermediates.
• Build structure–property and mechanistic models linking polymer chemistry to biodegradation and performance.
• Apply molecular modeling, thermodynamics, and kinetics to understand polymer–solvent and polymer–enzyme interactions.
• Integrate experimental, literature, and computational data into technical recommendations for polymer design and sustainability.

Skills

Molecular Dynamics

Free Energy Calculations

Enhanced Sampling Techniques

Programming

Education

Ph.D.

Job description

The University of Cincinnati, through the P&G Digital Accelerator@UC, invites applications for a postdoctoral researcher focused on computational modeling of polymer biodegradation and performance polymer behavior. The researcher will be employed by the University of Cincinnati and collaborate closely with P&G and UC technical teams.

Addressing high‑impact sustainability and performance challenges using applied computational modeling.