PhD: Coupling AI and Unit Operations in Process Systems Engineering

This PhD position at the Laboratory of Chemical Engineering of Institut National Polytechnique de Toulouse offers an exciting opportunity to explore the integration of artificial intelligence with process systems engineering. The project focuses on bridging the gap between data-driven machine learning models and fundamental physical laws governing chemical transformations and unit operations. The successful candidate will investigate methodology definition, applicability boundaries, and reliability limitations of digital tools in engineering applications. Throughout the three-year doctoral program, the researcher will utilize process simulation software, surrogate modeling tools, and advanced coding languages.

• Design and implement methodologies that couple AI data-driven tools with chemical transformation process systems.
• Develop and analyze machine learning algorithms and statistical approaches for engineering data treatment.
• Evaluate data-driven models to ensure compliance with fundamental physical conservation laws.
• Define applicability boundaries for the transition from phenomenological models to data-driven models.
• Utilize process simulation and surrogate modeling software throughout the research cycle.
• Publish research findings in peer-reviewed journals and present results at scientific conferences.