PhD on hybrid modelling and agentic process intensification

Our group at KU Leuven works at the interface of chemical engineering, process systems engineering and artificial intelligence. We develop hybrid models, digital twins and data-driven tools for process design, optimisation and control, with a strong focus on industrially relevant applications.
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Project

Within EL4CHEM, the researcher will develop methods for efficient knowledge transfer between processes, operating conditions and modelling scales. The work will involve hybrid modelling, transfer learning, uncertainty analysis and adaptive model updating for chemical and pharmaceutical processes.

Profile

We are looking for a candidate with a background in chemical engineering, process engineering, applied mathematics, computer science or a related field. Experience with Python, process modelling, machine learning or optimisation is an advantage. The candidate should be motivated, independent and interested in interdisciplinary research.

Offer

We offer a full-time research position for one year, with the possibility of extension up to four years, depending on performance and available funding. You will work in an international and multidisciplinary environment with opportunities for scientific publication, industrial collaboration and professional development.

Interested candidates can contact Prof. Mumin Enis Leblebici for further information.

Interested?

For more information please contact Prof. dr. Mumin Enis Leblebici, mail: [email protected].

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