- Assist in the research, design, and implementation of Graph Neural Networks (GNNs) and related models for real-world problems.
- Develop and implement node embedding techniques (e.g., DeepWalk, Node2Vec, GraphSAGE) to generate high-quality vector representations for graph nodes.
- Work with large-scale graph-structured data in the domain of sustainability.
- Modify ontology to address use-cases.
- Participate in experiments to test new graph-based machine learning methods, optimizing for both performance and accuracy.
- Collaborate with team members to integrate graph-based models into existing machine learning pipelines and production systems.
- Stay up-to-date with the latest research and advancements in the field of graph-based machine learning.
x
