Privacy-Preserving AI and Knowledge Graphs for Energy Digital Twins

Are you passionate about Artificial Intelligence, Knowledge Graphs, Knowledge Representation and Reasoning, and responsible data sharing?

Privacy-Preserving AI and Knowledge Graphs for Energy Digital Twins

Do you want to contribute to the future of sustainable energy systems while addressing fundamental challenges in privacy, trust, and explainability?

A 4-year full-time, fully-funded PhD position is available at the Knowledge in Artificial Intelligence (KAI) group and the User-Centric Data Science (UCDS) group of the Vrije Universiteit Amsterdam, in close collaboration with TU Delft and societal partners including the Municipality of Alkmaar and Arnhem Electricity Campus, as part of the NWO-funded KIC project FEDERATE: Fair Energy Data Environments for Renewable Autonomous Twin Empowerment.

The energy transition increasingly relies on data-driven digital twins that integrate information from municipalities, energy providers, grid operators, and other stakeholders. While sharing data enables better planning, optimization, and decision-making, it also raises important challenges regarding privacy, data ownership, regulatory compliance, and trust.

As a PhD candidate, you will develop novel AI and semantic technologies for privacy-preserving knowledge sharing in federated energy-data environments. Your research will focus on combining knowledge graphs, ontologies, knowledge representation and reasoning, machine unlearning, and formal reasoning to enable the selective removal of sensitive information while preserving the usefulness of shared knowledge.

Your duties

You will investigate how formal forgetting techniques, such as uniform interpolation and ontology forgetting, can be adapted to large-scale knowledge graphs and digital twins. In particular, you will explore:

• Modular ontology engineering and sensitivity modelling for energy-data ecosystems
• Formal forgetting and machine unlearning techniques for knowledge graphs and ontologies
• Temporal unlearning mechanisms for enforcing data-retention and privacy policies
• Privacy-preserving reasoning and federated knowledge graph infrastructures
• Formal verification techniques to certify that deleted knowledge cannot be reconstructed through logical inference
• Neuro-symbolic or machine unlearning approaches for privacy preserve
• Auditable and GDPR-compliant AI systems for trustworthy data sharing

The project combines theoretical advances in Knowledge Representation and Reasoning with real-world validation in energy-transition use cases. You will collaborate closely with researchers from Vrije Universiteit Amsterdam and TU Delft, as well as stakeholders from municipalities and energy innovation ecosystems.

Towards the end of your PhD, you will evaluate your methods in realistic pilot environments involving municipal and energy-campus data, contributing directly to trustworthy and responsible AI solutions for the energy transition.

Our PhD students are expected to publish their research at leading venues in Artificial Intelligence, Knowledge Representation, Semantic Technologies, and Machine Learning, including AAAI, IJCAI, ECAI, NeurIPS, ICML, ICLR, ACL, EMNLP, KR, ISWC, ESWC, The Web Conference (WWW), and other top international conferences and journals.

Your profile

KAI and UCDS are internationally recognized research groups with a strong track record in Artificial Intelligence, Knowledge Representation and Semantic Technologies, Human-Centred AI, Semantic Web technologies, Knowledge Graphs, and responsible data-driven systems.

We are looking for a highly motivated PhD candidate with the following qualifications:

• A Master’s degree (or equivalent) in Computer Science, Artificial Intelligence, Data Science, Information Science, Mathematics, or a closely related field
• Strong interest in Artificial Intelligence, knowledge representation and reasoning, and semantic technologies
• Background in one or more of the following areas:

• Knowledge Representation and Reasoning, computational logic, especially forgetting/uniform interpolation, Craig Interpolation, concept interpolation, etc.
• Semantic Web Technologies
• Machine Learning and Explainable AI
• Data Privacy and Security

• Solid programming skills, e.g., in Python and/or Java
• Good communication skills in English (written and spoken)
• Strong analytical and problem-solving skills
• Previous research experience in related topics is considered a plus

Supervision

The PhD candidate will be supervised by:

• Dr. Jieying Chen (Vrije Universiteit Amsterdam)
• Dr. Ronald Siebes (Vrije Universiteit Amsterdam)
• Dr. Victor de Boer (Vrije Universiteit Amsterdam)

The successful candidate will become part of a vibrant interdisciplinary team working at the intersection of Artificial Intelligence, Knowledge Representation, Semantic Technologies, Privacy-Preserving AI, and Digital Twins for the Energy Transition.

We realise that each individual brings a unique set of skills, expertise and mindset. Therefore we are happy to invite anyone who recognises themselves in the profile to apply, even if you do not meet all the requirements.

What do we offer?

A challenging position in a socially engaged organisation. At VU Amsterdam, you contribute to education, research and service for a better world. And that is valuable. So in return for your efforts, we offer you:

• an employment contract of initially 18 months. If there is sufficient perspective, this will be extended to a total of 4 years. Your dissertation at the end of the fourth year forms the end of your employment contract.
• 8% holiday allowance and 8.3% end-of-year bonus
• contribution to commuting expenses
• optional model for designing a personalized benefits package
• certain tax benefits (30% ruling) might apply to international candidates

About us

About the department

The VUA Department of Computer Science has approximately 170 members, including 35 tenured staff members and 90 PhD students.

Faculty of Science

Working at the Faculty of Science means collaborating with students, lecturers and researchers who are focused on their field, yet have a broad view of the world. We are proud of a positive and inclusive workplace culture within the faculty, where we work together with great energy and a pragmatic attitude to tackle social challenges. At the Faculty of Science, scientists and students work on fundamental and complex societal issues for a sustainable, healthy and just future.

Our academic education and research are highly experimental, technical and interdisciplinary in nature. That is why we collaborate extensively with leading scientific institutes and industry.

Vrije Universiteit Amsterdam

Vrije Universiteit Amsterdam stands for values-driven education and research. We are open-minded experts with the ability to think freely. Maintaining an entrepreneurial perspective and concentrating on diversity, significance and humanity, we work on sustainable solutions with social impact. By joining forces, across the boundaries of disciplines, we work towards a better world for people and planet. Together we create a safe and respectful working and study climate, and an inspiring environment for education and research.