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Data science frontier: theory and algorithm

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Theoretical breakthroughs in frontier data science will be built on top of statistic learning and deep learning for complex data analytics and learning. Typical issues include learning theories for non-IID big data that is heterogeneous and coupled with complex relations from attribute values to objects.

Interested candidates must have solid background knowledge in statistics/mathematics, data science and artificial intelligence (in particular statistics, machine learning, data mining and pattern recognition), a master by research qualification, and demonstrated research capabilities (through publications). Candidates are expected to have publications with major conferences/journals.

The candidates will work at the Data Science Lab at UTS Advanced Analytics Institute, an active team with strong research culture and track record in quality and impact-driven research and engagement with many major local and international partners. Successful candidates may have opportunities to work with international leaders in the area.

Funding Notes

Value: $27,082 pa (tax-exempt)

Duration: 3 yrs

School/Centre: School of Computer Science/ Advanced Analytics Institute

Enquiries: Professor Longbing Cao - please send CV, publications and research plan if interested

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