Postdoc: AI-Driven Automated Materials Discovery

University of Delaware; Newark (NJ); On-site; USD 55,000 - 75,000; Full time

Job summary

The University of Delaware in Newark, DE seeks a Postdoctoral Researcher to develop automated workflows that integrate AI/ML with laboratory experiments for the Center for Clean Hydrogen’s AEM Moonshot project. You will build data pipelines, connect measurements with predictive models, and collaborate with chemists, materials scientists, and engineers to accelerate discovery of high‑conductivity, durable AEMs.

Some evenings/weekends may be required.

Qualifications

• PhD required by start date in a relevant field such as chemical engineering, materials science, chemistry, electrical engineering, mechanical engineering, or computer science.

Responsibilities

• Develop automated experimental workflows, including instrument integration, data acquisition, and analysis.
• Integrate AI/ML models with experiments to predict material properties and guide candidate selection through active learning and uncertainty-informed decision-making.
• Build reproducible data pipelines connecting experimental measurements, computational results, and shared project datasets.
• Collaborate with project partners to validate predictions and investigate relationships among polymer chemistry, structure, conductivity, and stability.
• Work with project partners to scale up promising candidates to deployable devices.
• Maintain experimental records, document software and laboratory protocols, and prepare manuscripts for publication.
• Ensure proper use and maintenance of laboratory equipment, support student researchers, and follow applicable laboratory safety procedures.

Skills

Python

AI/ML for science

Lab automation

Data pipelines

Education

PhD in related field

Job description

The University of Delaware in Newark, DE seeks a Postdoctoral Researcher to develop automated workflows that integrate AI/ML with laboratory experiments for the Center for Clean Hydrogen’s AEM Moonshot project. You will build data pipelines, connect measurements with predictive models, and collaborate with chemists, materials scientists, and engineers to accelerate discovery of high‑conductivity, durable AEMs.

Some evenings/weekends may be required.