PhD Position in Machine Learning and Process Optimization for Sustainable Water (ref. BAP-2025-620)

As a PhD researcher, you will: Build and validate hybrid models for photocatalytic processes.Apply machine learning to experimental datasets from consortium partners.Develop and implement multi-objective optimization algorithms (e.g., NSGA-II, MOPSO).Collaborate closely with international teams from FEUP, NTNU, CSIC, and NRC.Contribute to publications, conferences, and the development of scalable solutions for sustainable water-energy systems.

Are you passionate about sustainability, clean energy, and water treatment technologies?Are you skilled in machine learning, process modelling, or chemical engineering simulations?Are you excited by the idea of working in a multidisciplinary, international consortium?Are you familiar with Python, MATLAB, or similar tools for data analysis and optimization?Are you eager to contribute to EU-wide goals on energy neutrality and circular economy?Are you motivated to publish in high-impact journals and present at international conferences?Are you ready to take initiative, work independently, and collaborate across borders?, Master's degree in Chemical Engineering, Process Engineering, Computer Science, or related fields.

Strong background in modelling, simulation, and/or machine learning.

Experience with data preprocessing, algorithm development, and optimization techniques.

Excellent communication skills in English.

Prior experience with environmental or photocatalytic systems is a plus.

At KU Leuven, our team, lead by Prof. Enis Leblebici focuses on the development of advanced modelling, simulation, and optimization techniques for chemical and environmental processes. We specialize in hybrid modelling, machine learning, and optimization, with applications ranging from complex process optimization to process intensification. Our team is interdisciplinary, collaborative, and committed to solving real-world challenges through cutting-edge research. Alumni of Prof. Leblebici have gone on to prestigious postdoctoral fellowships (including MSCA and FWO), and now hold elite positions in government agencies, academia, and industry. Project About the AQUAEra Project: AQUAEra is a transnational EU-funded project under the Water4All Partnership, aiming to revolutionize urban wastewater treatment by integrating advanced oxidation processes (AOPs), photocatalysis, and renewable energy generation.KU Leuven leads Modelling and Optimization, which focuses on: Developing hybrid models combining first-principle and machine learning approaches. Creating predictive frameworks for photocatalytic degradation and H2 production.Designing multi-objective optimization algorithms to maximize environmental and economic performance.