Research Associate — ML & Digital Twin for Process Systems

Worcester Polytech; Worcester (MA); Hybrid; USD 55,000 - 65,000; Full time

Job summary

Worcester Polytechnic Institute (WPI) in Worcester, MA, seeks a Postdoctoral Research Associate to develop machine learning and agentic AI methods for chemical and environmental engineering applications. You will work closely with chemical engineers to develop hybrid physics- and data-driven models, digital twins, and autonomous workflows for complex reaction and process systems.

The role emphasizes advancing ML applications in engineering, building digital twins, and integrating AI with

Qualifications

• PhD in Chemical Engineering, Engineering, Applied Mathematics, Data Science, Computer Science, Operations Research, or closely related field.
• Demonstrated experience applying machine learning to physical, engineering, or scientific systems.
• Strong proficiency in Python and modern machine learning frameworks.
• Experience developing regression, surrogate, optimization, or uncertainty quantification models for engineering applications.
• Publication record in ML, scientific computing, process systems engineering, or a related field.

Responsibilities

• Collaborate with chemical engineers to develop hybrid physics- and data-driven models.
• Develop digital twins and autonomous workflows for complex reaction and process systems.
• Publish findings and contribute to ongoing research in process systems engineering.

Skills

Python

Machine learning frameworks

Regression models

Optimization/Uncertainty quantif.

Publication track record

LLMs / agentic AI

Education

PhD in Chemical Engineering

Tools

Aspen Plus

gPROMS

COMSOL

Cantera

Job description

Worcester Polytechnic Institute (WPI) in Worcester, MA, seeks a Postdoctoral Research Associate to develop machine learning and agentic AI methods for chemical and environmental engineering applications. You will work closely with chemical engineers to develop hybrid physics- and data-driven models, digital twins, and autonomous workflows for complex reaction and process systems.

The role emphasizes advancing ML applications in engineering, building digital twins, and integrating AI with