[Opt-Net] PhD scholarship at RMIT University

[Andrew Eberhard]

Could you please post the following PhD scholarship advertisement  on
Opt-net Digest,

Regards,
Prof. Andrew Eberhard


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PhD Project: Decomposition and Duality: New Approaches to
Integer and Stochastic Integer Programming

RMIT University: School of Mathematical and Geospatial Sciences

A stipend for this project will be paid under ARC Discovery Project
DP140100985:
Tuition fees will be covered and the successful applicant will receive
$28,392p.a.

Applications for this PhD scholarship will be accepted until a suitable
applicant has been found.

Background:

The successful applicant will join a team of postdocs and researchers at
RMIT University and the
University of Newcastle working on of this project. This PhD scholarship
will be administered at
RMIT and the student will work under the supervision of Prof. Andrew
Eberhard and Prof. Natashia
Boland.

One of Australia’s original educational institutions founded in 1887, RMIT
is now the nation’s largest
tertiary institution. The University offers an extensive range of
postgraduate, undergraduate and
vocational programs.  The School of Mathematical & Geospatial Sciences
draws together disciplines
involving the collection of data with the analysis of data and the
understanding and optimisation of
systems through modelling and visualisation.  The School has about 50
academic staff and over 70
postgraduate research students. RMIT is a founding member of the
Australasian Mathematical
Sciences Institute and was ranked 4 and the top in Victoria in Applied
Mathematics in the last ERA
round.  Newcastle has been ranked 5 in Applied mathematics in the last two
ERA rounds.

Project aims:

Because of their rich modelling capabilities, integer programs are widely
used in industry for decision
making and planning. However their solution algorithms do not have the
maturity of their cousins in
convex optimization, where the theory of strong duality is ubiquitous.
Efficient methods for convex
optimization under uncertainty do not apply to the integer case, which is
highly nonconvex.
Furthermore integer models usually assume the data is known with certainty,
which is often not the
case in the real world. This project looks towards the development of new
theory and algorithms to
enhance the analysis of integer models, including those that incorporating
uncertainty, while also
enabling the use of parallel computing paradigms.

Desired Skill Set:

We are looking for a good student with strong mathematical, computational
and
programming skills. An interest and willingness in learning new theory and
methods. A
background in optimization theory and a sound grounding in modern
programming languages
is desirable.

Contact:
Prof. Andrew Eberhard
andy.eberhard at rmit.edu.au
+61 3 9925 2616

and/or

Prof. Natashia Boland
Natashia.Boland at newcastle.edu.au
+61 2 4921 6717

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