PhD Candidate on Multi-Objective Optimization and Machine Learning for Hydrogen

The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a:

PhD Candidate on Multi-Objective Optimization and Machine Learning for Hydrogen Technologies

Hydrogen-related equipment (such as compressors, electrolysers, and purity measurement instruments) must be utilized safely, in an environmentally friendly manner, and at low cost to effectively and sustainably advance green energy transition. Implementing multi-objective optimization enables the generation of Pareto optimal solutions to address multiple conflicting goals related to utilization and maintenance plans. Machine learning algorithms play a crucial role in predicting equipment lifetime and performance, as well as detecting abnormalities by analyzing historical and real-time operational data.

This project aims to develop an automated machine learning methodology capable of learning from historical and real-time operational data of hydrogen equipment. This methodology will enable prediction of degradation and lifetime, anomaly detection, and identification of potential disruption risks. These predictions will then by utilized as inputs for a multi-objective optimization model aimed at optimizing maintenance plans for Hydrogen associated equipment, including compressors, electrolyzers, and purity measurement instruments. Hyper-parameter optimization will be used to ensure the methodology fits different types of equipment and various conditions. Furthermore, the project aims to visualize solutions in a manner that is easily interpreted by decision-makers.

We are looking for a candidate who is a self-motivated and creative researcher with expertise in both multi-objective optimization and machine learning. Industrial experience is highly valued. You will be working with the Natural Computing Group of LIACS at Leiden University and closely collaborate with hydrogen technology companies and other universities in the Netherlands.

Key responsibilities

• Conduct original and novel research in the field of multi-objective optimization and machine learning for hydrogen associated equipment;
• Publish and present scientific articles at international journals, conferences, and workshops;
• Collaborate with hydrogen technology companies and researchers of other universities in the Netherlands;
• Assist in relevant teaching activities;

 

Selection Criteria

We are looking for a candidate that meets the following criteria:

• MSc degree in Artificial Intelligence, Data Science, Applied Mathematics, Computer Science, or a related field;
• Solid experience in multi-objective optimization and machine learning;
• Excellent programming skills, particularly in Python;
• Self-motivated and creative with industrial experience;
• Excellent written and oral communication skills in English; Dutch proficiency or willingness to learn is a plus;
• Ability to collaborate effectively with diverse stakeholders, including industry professionals and academic researchers;

Research at our faculty

The Faculty of Science is a world-class faculty where staff and students work together in a dynamic international environment. It is a faculty where personal and academic development are top priorities. Our people are committed to expand fundamental knowledge by curiosity and to look beyond the borders of their own discipline; their aim is to benefit science, and to make a contribution to addressing the major societal challenges of the future.

The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and environmental sciences. The research activities are organised in eight institutes. These institutes offer eight bachelor’s and twelve master’s programmes. The faculty has grown strongly in recent years and now has more than 2.800 staff and almost 6,000 students. We are located at the heart of Leiden’s Bio Science Park, one of Europe’s biggest science parks, where university and business life come together. For more information, see

and
The Leiden Institute of Advanced Computer Science (LIACS) is the Artificial Intelligence and Computer Science Institute in the Faculty of Science of Leiden University. We offer courses at the Bachelor and Master of Science level in Artificial Intelligence, Computer Science, ICT in Business, Media Technology, and Bioinformatics. According to an independent research visitation, we are one of the foremost computer science departments of the Netherlands. We strive for excellence in a caring institute, where excellence, fun, and diversity go hand in hand. We offer a clear and inviting career path to young and talented scientists with the ambition to grow. For more information about LIACS, see

Terms and conditions

We offer a full-time 1-year term position for initially one year. After a positive evaluation of the progress of the thesis, personal capabilities and compatibility the appointment will be extended by a further three years. Salary ranges from € 2.770, - to € 3.539, - gross per month (pay scale P in accordance with the Collective Labour Agreement for Dutch Universities).

Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses (8.3%), training and career development and sabbatical leave. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside the Netherlands may be eligible for a substantial tax break.

All our PhD students are embedded in the Leiden University Graduate School of Science
. Our graduate school offers several PhD training courses at three levels: professional courses, skills training and personal effectiveness. In addition, advanced courses to deepen scientific knowledge are offered by the research school.

D&I statement

Diversity and inclusion are core values of Leiden University. Leiden University is committed to becoming an inclusive community which enables all students and staff to feel valued and respected and to develop their full potential. Diversity in experiences and perspectives enriches our teaching and strengthens our research. High quality teaching and research is inclusive.

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