(Apologies for cross posting. This project also has open PhD positions.)

Postdoctoral fellow open in the "Democratising Big Machine Learning"
project in the Department of Computing and Information Systems at the
University of Melbourne, Australia.

The project is on machine learning and systems for data preparation. Topics
span probabilistic databases, data integration/entity resolution, adaptive
importance sampling for crowd sourcing, ML workflows – it is expected the
candidate would work in one of these areas or related, but likely not all.

Ideal candidates would have strong background in some of: Bayesian
inference, probabilistic graphical models, optimisation, linear algebra,
mathematical statistics, experimental design, databases (the probabilistic
kind and otherwise), cloud platforms like EC2/Azure. A strong mathematical
background is a must. The project involves systems building; a major
activity will be publishing.

The  project's sole-CI Ben Rubinstein is a junior faculty member in the
department (Assistant Professor equivalent) with a PhD from Berkeley and
3yrs as Researcher at the Microsoft Research Silicon Valley lab. He has
worked in many of the major industry research labs, and has served on the
PCs of many of the major ML, AI, DB conferences. The group has strong
connections and support from industry, specifically for this project (with
significant time on Azure). The project is fully funded by the ARC
(Australia's NSF). The broader group at Melbourne is very strong, eg
hosting both SIGMOD and CIKM this year, and with ties with an exceptional
mathematical statistics group at Melbourne lead by Peter Hall. The
University of Melbourne is ranked as the top in Australia, and among the
top 30-40 institutions internationally, while the city of Melbourne is
consistently ranked among the top handful of most liveable cities for its
exceptional quality of life.

The position is funded for 1 year with a competitive salary of $80k AUD
plus 17% superannuation.

For more:

Email Ben Rubinstein [log in to unmask]