AUT019 - Automated Completion and Adjustment for Knowledge Graph

Description: Knowledge Graphs (KGs) have found many applications in industry and academic settings, which in turn, have motivated considerable research efforts towards large-scale information extraction from a variety of sources. In this project, we aim to construct high-quality domain-specific KGs from unstructured big data and explore hidden knowledge from the constructed KGs. This is an interdisciplinary research, including AI, NLP and network science.

Skills requirement: 1.  A background in computer science, artificial intelligence or software engineering.
2.  STRONG programming skills (JavaScript, Java, Python). Candidates with industrial experience - software development, are preferred.
3.  Comfortable with mathematics, machine learning and algorithms development.
4.  Positive, enthusiastic, self-motivated and hardworking

Department: School of Engineering, Computer & Mathematical Sciences

Type: PhD, Expressions of Interest

Scholarship: The project is undertaken in collaboration with an AI company in Auckland, New Zealand. The funding is confirmed. The successful candidate will be granted a STIPEND of $26K NZD/year, up to 3 years.

Applicants will need to satisfy AUT’s admissions criteria and hold an appropriate visa at the time of application.