Research Fellow / Postdoc, PhDVisiting Student, positions available!

Research Postdoc in ARC Discovery — Machine learning, recommender system, intelligent assistant

* Full time – 2-3 years Fixed term/Contract
* $96,564 – $114,672 + 17% super, flexible working arrangements on offer.
* Convenient Central City Location in Melbourne, One of The World’s Most Liveable Cities
Apply here

Applications close on 21 Jan 2020 11:55 PM AUS Eastern Daylight Time (GMT+11).

The Role
This is an exciting opportunity for a Research Fellow to work within the research team from RMIT, with Assoc. Prof Flora Salim and Dr. Yongli Ren, in collaboration with Prof Cecilia Mascolo from University of Cambridge and Prof Charlie Clarke from University of Waterloo, on the Australian Research Council Discovery project “Multi-resolution Situation Recognition for Urban-Aware Smart Assistant”. This project will develop a new situation recognition and recommender systems framework that is resilient to urban disruptions.

Visiting Research Fellow/Student in Trajectory Data Mining

A 3-4 month visiting fellow position is available for an excellent postdoc/PhD student in trajectory data mining.  The candidate’s role is primarily to plan, develop and engage in spatio-temporal data mining and applied machine learning research using several large-scale mobile trajectory datasets. The  candidate will be expected to produce high quality outputs in A/A* journal / conference outlets.

The candidate needs to be highly skilled in machine learning in python and have sound knowledge in statistics, data modelling, and have worked with recent deep learning models. Experience with processing and analysing large scale spatio-temporal data is desirable.

The scheme is primarily intended for PhD students (who have already passed their Qualification Exam or Confirmation of Candidature at their respective university) or for postdocs who seek to conduct joint research in trajectory data mining and machine learning.

We will cover return airfares and living allowance at competitive rates.

Flora is also an eligible host for Humboldt fellows as an outgoing Humboldt alumni from March 2020. She is also eligible to be a host for DAAD fellows.

To apply, contact Dr. Flora Salim

PhD Scholarship

Scholarships in four PhD topics are available:

  1. Scalable and Transferrable Occupant Behaviour Learning with Multi-Sensor Data from Multi-region Living Labs co-supervised by Prof Mikkel Kjaergaard, University of Southern Denmark
  2. Efficient Temporal Segmentation in Mining Big Time Series for Accurate Prediction of Heterogeneous Activities and Events, co-supervised by Prof Eamonn Keogh, UC Riverside
  3. Spatio-temporal Analytics and Deep Learning of Big Trajectory Data for Situation Awareness, co-supervised by Dr. Jeffrey Chan, RMIT University
  4. Cross Domain Data Fusion and Analytics of User Contexts and Behaviours for Personalized Recommendation Systems, co-supervised by Dr. Yongli Ren, RMIT University

PhD and Scholarship Application Process

Closing dates: Check RMIT closing dates.