Research Associate

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. 

Please attach a CV, cover letter and contact information for three references.