Graph Machine Learning Research Intern

Physics World is seeking a Graph Machine Learning Research Intern for their Summer Internship Program. The role involves leading research in graph computing, designing algorithms for graph representation learning, and applying GML to various high-impact domains.

Responsibilities:

• Lead and contribute to cutting-edge research in graph computing and graph machine learning (GML)
• Design, develop, and evaluate algorithms for graph representation learning, reasoning, and analytics on dynamic, heterogeneous, and large-scale graphs
• Apply GML to high-impact domains such as cybersecurity, finance, social science, material science, and intelligent systems
• Integrate GML with foundation models (e.g., large language models/LLMs, multimodal models) for tasks like knowledge graph reasoning, graph-augmented retrieval, and trustworthy decision support
• Translate research insights into deployable prototypes and production-level software
• Author technical publications, invention disclosures, and research presentations for internal and external stakeholders, and support proposal and business development activities