Postdoc in Scalable Graph Learning

Postdoc in Scalable Graph Learning at TU Delft

Job description

Graph machine learning (Graph ML) is a rapidly growing field of artificial intelligence (AI), driven by the widespread presence of graph-structured data in many real-world scenarios. Graph neural networks (GNNs) are at the core of this emerging field and have proven effective in a range of applications, including recommender systems, financial crime detection, cybersecurity, and the analysis of social, biological, and chemical networks.

This project focuses on applications of GNNs to financial domains, particularly in analyzing financial transaction networks to uncover illicit activities such as money laundering and financial fraud. We will explore new ways of integrating GNNs and Large Language Models (LLMs) to construct machine learning solutions capable of exploiting graph-structured data with rich sets of node and edge features. Additionally, this project will address challenges related to scalability, efficiency, privacy, and resilience against adversarial attacks.

Delft University of Technology (TU Delft) is seeking applications for a postdoctoral researcher in the area of Scalable Graph Learning, within the Department of Software Technology in the Faculty of Electrical Engineering, Mathematics, and Computer Science.

About the Research Group

The Scalable Graph Learning Group, led by Associate Professor Kubilay Atasu, is part of the Data-Intensive Systems Section. Established in 2024, the group focuses on both theoretical and practical aspects of Graph Machine Learning, including:

• Algorithmic efficiency
• Expressiveness
• Scalability
• Real-world applications

Assoc. Prof. Atasu joined TU Delft following a successful research career at IBM Research.

The Department Software Technology

The Department of Software Technology (ST) is one of the leading Dutch departments in research and academic education in computer science, employing over 150 people. The department ST is responsible for a large part of the curriculum of the bachelor’s and master’s programmes in Computer Science as well as the master’s programme in Embedded Systems. The inspiration for its research topics is largely derived from technical ICT problems in industry and society related to large-scale distributed processing, embedded systems, programming productivity, and web-based information analysis.

Job requirements

We are looking for a candidate who satisfies the following requirements:

• a PhD degree in Computer Science, Mathematics, Electrical Engineering or a related discipline with a PhD thesis conducted in the field of machine learning, deep learning, or parallel & distributed computing,
• experience in the field of graph machine learning, federated learning, differential privacy, or adversarial robustness,
• hands-on experience with Deep Neural Networks using PyTorch or TensorFlow, and preferably with GNNs using Pytorch Geometric or Deep Graph Library.
• first-author publications at leading conferences in artificial intelligence, machine learning, security and privacy, or data management.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Conditions of employment

• Duration of contract is 18 months.
• A job of 36-40 hours per week.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Additional information
If you would like more information about this vacancy or the selection procedure, please contact Dr. Kubilay Atasu, via Kubilay.Atasu@tudelft.nl