Department of Computer Science

Responsibilities

• Assist in the collection and pre-processing of various graph datasets under different noise levels and types;
• Support the investigation and analysis of graph properties beyond homophily;
• Aid in the implementation and testing of graph mining modules and the trustworthy propagation module under the guidance of the Principal Investigator;
• Conduct experimental studies, run baseline comparisons, and assist in the systematic evaluation of the developed graph-based learning system;
• Prepare documentation and reports on the implemented methods and experimental results.

Requirements

• Currently pursuing a postgraduate degree (MPhil or PhD) or a recent graduate with a bachelor’s, master’s or PhD degree in computer science, artificial intelligence, data science, or a closely related field;
• Solid background in graph theory, machine learning, and deep learning;
• Proficiency in programming languages such as Python and experience with deep learning frameworks (e.g., PyTorch, TensorFlow);
• Experience with graph analysis libraries (e.g., NetworkX, PyTorch Geometric, DGL, etc.) is highly desirable;
• Strong analytical and problem-solving skills;
• Good command of written English.

Interested parties please send full resume with salary expectation and availability by clicking Apply.

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