Research Associate

Worcester Polytechnic Institute; Worcester; On-site; GBP 42,000 - 49,000; Full time

Benefits offered by this job

Retirement match

Wellness perks

Tuition assistance

Job summary

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

The role emphasizes developing regression and surrogate models, uncertainty quantification and integration with process simulators, with a competitive salary

Qualifications

• Ph.D. 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 ML frameworks.

Responsibilities

• Develop machine learning and agentic AI methods for chemical and environmental engineering applications.
• Create hybrid physics- and data-driven models, digital twins and autonomous workflows for complex reaction and process systems.
• Collaborate with chemical engineers to advance modeling, simulation and optimization capabilities.

Skills

Python

ML frameworks

Regression/Surrogate models

Uncertainty quantification

Education

Ph.D. in Chemical Engineering or closely related field

Tools

Aspen Plus

gPROMS

COMSOL

Cantera

Job description

JOB TITLE

Research Associate

LOCATION

Worcester

DEPARTMENT NAME

Chemical Engineering - NFR JM

DIVISION NAME

Worcester Polytechnic Institute - WPI

JOB DESCRIPTION SUMMARY

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.

JOB DESCRIPTION

Required Qualifications

• 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.

Preferred Qualifications

• 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.
• Preference for candidates with research experience in process systems engineering, process modeling and simulation, reaction engineering, scientific machine learning, or digital twin development.

Compensation:

Salary: $55,000 to $65,000 per year. Salary is based on related experience, expertise, and internal equity. WPI's includes a robust retirement match, wellness perks, tuition assistance and more!

FLSA STATUS

United States of America (Exempt)

WPI is an Equal Opportunity Employer. All qualified candidates will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. It seeks individuals from all backgrounds and experiences who will contribute to a culture of creativity, collaboration, inclusion, problem solving, innovation, high performance, and change making. It is committed to maintaining a campus environment free of harassment and discrimination.