PhD/Visitor Positions

Trustworthy AGI Lab (TrustAGI) at Griffith University is a top research lab focusing on trustworthy artificial general AI research.

We am looking for self-motivated Ph.D students funded by: (1) Griffith University, (2) Australian Research Council, (3) Other funders (e.g., CSC)

Multiple Phd positions are available. Applicants currently in Australia are especially welcome! Drop us an email now!

We have multiple visitor positions each year. Contact us if a) your backgournds aligns well with ours, b) you are self-funded.


Griffith Uni ranks in the top 2 percent of universities globally with 50000 students spanning six campuses in South East Queensland, Australia. The Computer Science & Engineering at Griffith ranks in the top 76-100 globally.

  • Times Higher Education Young University Rankings:33
  • QS World University Rankings Top 50 Under 50 :33
  • US News Best Global Universities: 201
  • Times Higher Education World University Rankings: 201–250

Research Group

Group members can be found here. This TrustAGI lab mainly focuses on data mining, machine learning, NLP, deep learning, graph data analytics, and AI applications. The research group consists of a number of Phd students working on the following area (Potential PhD/minor thesis/honours research topics include but are not limited to):

  • Large Language Models (LLMs)
    1. LLMs for time series analysis
    2. LLMs for graph analysis
    3. LLMs and knowledge graphs
    4. LLMs for drug discovery
  • Graph & Network Analytics
    1. Graph Nerual Networks
    2. Graph Attack and Defence
    3. Social Recommendation
    4. Knowledge Graphs
    5. Graph Embedding
  • Deep Learning
    1. AutoML (Neural Architecture Search)
    2. Adversarial deep learning
    3. Deep learning for graph Data
    4. Deep spatial temporal modeling
    5. Deep reinforcement learning
  • NLP
    1. Sentence embedding
    2. Attention network
    3. Text classification
    4. Question Answering
  • Time Series/Streaming Data Analytics
    1. Time series feature selection
    2. Time series prediction
    3. Data stream/concept drift
  • Anomaly Detection
    1. Outlier detection
    2. Novelty discovery
  • AI Applications
    1. Cyberbullying detection
    2. Suicidual detection
    3. Healthcare data analytics
    4. Recommender system
  • Trustworthy AI
    1. Fairness
    2. Explainability
    3. Robustness
    4. Privacy


  • A master degree with a computer science related background, and GPA > 85/100. Outstanding students with only undergraduate degree can also be considered, if GPA > 90/100.
  • Outstanding English skills, e.g., IELTS 6.5 overall (no band less than 6.0), TOEFL IBT 79 + (no sub-score less than 19), PTE 58 (no sub-score less than 50).
  • A good publication track record, demonstrated by publications.
    1. at least one paper published in CORE A*/A conference or JCR Q1 Journal, or
    2. at least one paper published in CCF A/B veneues


There is no deadline, and you can apply at anytime of the year!


Please send us your CV, transcripts, publication list, and research topics# (not have to be the one listed above) that you are interested in. Due to large number of applications, We may only reply to selected applicants.


Shirui Pan
Shirui Pan
Professor and ARC Future Fellow

My research interests include data mining, machine learning, and graph analysis.