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PhD Position in Machine Learning and Process Optimization for Sustainable Water

  • //applyindex.com/wp-content/uploads/2021/11/belgium.png Belgium
  • University/Institute Name KU Leuven
  • Attendance Type On Campus (Full Time)
  • Position DurationSee Position Description
  • Position Funding Type Marie Curie PhD Scholarship
  • Application deadlineJanuary 15, 2026
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Position Details (PhD Program)

About the Leblebici Team
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.

Your Role
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.

Profile

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?

Requirements

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.

Offer

A fully funded PhD position (salary according to KU Leuven standards). Access to state-of-the-art facilities and international collaboration. Opportunities for mobility, training, and participation in European workshops and schools. A dynamic and supportive research environment with strong mentorship.

Interested?

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

KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.

Research Areas & Fields of Study involved in the position

Position Start Date

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