Research Associate

WPI•Worcester, MA

29d•Onsite

About The Position

We seek a highly motivated Postdoctoral Research Associate to develop machine learning and agentic AI methods for chemical and environmental engineering applications. The successful candidate 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.

Requirements

Ph.D. in Chemical Engineering, Engineering, Applied Mathematics, Data Science, Computer Science, Operations Research, or a 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 machine learning, scientific computing, process systems engineering, or a related field.

Nice To Haves

Experience developing digital twins for engineering systems.
Experience integrating machine learning with mechanistic or first-principles models.
Experience with scientific machine learning, physics-informed ML, Bayesian methods, or uncertainty quantification.
Experience with Aspen Plus, gPROMS, COMSOL, Cantera, or related process simulation software.
Experience applying LLMs or agentic AI systems to scientific and engineering workflows.
Familiarity with TEA, LCA, process optimization, or reaction engineering.
Research experience in process systems engineering, process modeling and simulation, reaction engineering, scientific machine learning, or digital twin development.

Responsibilities

Develop machine learning and agentic AI methods for chemical and environmental engineering applications.
Work closely with chemical engineers to develop hybrid physics- and data-driven models, digital twins, and autonomous workflows for complex reaction and process systems.