Post-doctoral Research Fellowship in Online Learning and Graphical Models now available


Project: Online Learning for Large Scale Structured Data in Complex Situations
Duration: 2 years (renewable)
Salary: University Level B (AU$86,756~ 89,887 depending on qualifications), plus benefits. Funding for relocation and conference travel is available.

The project is run by Dr Qinfeng (Javen) Shi.

Online Learning (OL) is the process of predicting answers for a sequence of questions. OL has enjoyed much attention in recent years due to its natural ability of processing large scale non-structured data and adapting to a changing environment. We aim to develop theoretical and practical advances in OL for large scale structured data in complex situations. Probabilistic Graphical Models will be a key component in the project.

We expect the project will lead to publications in machine learning and computer vision conferences and journals. There will also be opportunities for joint supervision of postgraduate and honours level students, collaboration with the Centre, and with visitors and with international partners.

The successful applicant must have:
  • a PhD in a relevant discipline
  • a background in machine learning or computer vision, preferably including Online Learning and Probabilistic Graphical Models
  • experience in C++, Python and/or Matlab
  • a good publication record commensurate with experience
  • fluency in written and spoken English
  • the ability to work individually and as a member of a broader team


    The closing date for applications is 18 December, 2013. Please ensure that applications, together with a full CV (including a publication list and statement of research expertise and interests) and the names of two referees, are received by 5pm Australian Central Standard Time (UTC+9.30).

    Please email any queries or applications to Dr Qinfeng (Javen) Shi.

    Also see the job ad at ACVT