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PhD Position in Scalable Graph Learning
2 maanden geleden
Graph machine learning is an emerging field of artificial intelligence that deals with graph-structured data. Graph neural networks (GNNs) are a key technology in this area, used in various applications such as recommendation systems, financial crime analysis, and social network analysis. However, conventional GNN architectures have limitations in detecting complex graph patterns. This project aims to identify the trade-offs between combinatorial and neural-network-based approaches in the Graph ML space.
Key Objectives- To combine and unify combinatorial algorithms and GNNs based on linear-algebra-based primitives.
- To achieve more efficient and scalable solutions for graph pattern detection.
- To explore the capabilities of GNNs in solving combinatorial graph problems.
- To investigate the potential of offloading graph processing to AI accelerators.
- To develop distributed solutions for large graph datasets.
We are seeking a candidate with a strong background in algorithms and complexity analysis, as well as hands-on experience with Deep Neural Networks using PyTorch or TensorFlow. The candidate should have a solid understanding of graph theory and machine learning concepts. Good speaking and writing skills in English are also required.
Conditions of EmploymentThe PhD candidate will be offered a 4-year period of employment, with a 1.5-year contract followed by a 2.5-year contract. The salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customizable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
About TU DelftTU 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. At TU Delft, we value diversity and strive to create an inclusive environment where everyone feels at home and can flourish.
