Two optimisation positions at Curtin.
Curtin has two optimisation positions open:
level D/E with particular emphasis on industry engagement
and
Mathematics of Computation and Optimisation
Special Interest Group of the AustMS
Curtin has two optimisation positions open:
level D/E with particular emphasis on industry engagement
and
Registration and abstract submission are now open for the 65th meeting of Australian Mathematical Society, to be held online 7–10 December 2021.
Confirmed plenaries for the optimization special session are Professor Radu Ioan Boţ (Universität Wien) and Levent Tuncel (University of Waterloo).
We look forward to seeing you there.
Save the date! The 65th Annual Meeting of the Australian Mathematical Society will feature a special session on Optimisation. The conference will be held online, from Tuesday, 7 December to Friday, 10 December, 2021. Registration and abstract submission will be open soon. You can follow the AustMS website or the CARMA website for further information.
Special session organisers:
Scott B. Lindstrom: scott.lindstrom@curtin.edu.au (Curtin University),
Hoa Bui: hoa.bui@curtin.edu.au (Curtin University) and
Reinier Diaz Millan: r.diazmillan@deakin.edu.au (Deakin)
The Workshop on Optimisation, Metric Bounds, Approximation and Transversality will be held online on 13–17 December 2021.
Confirmed Keynotes: Regina Burachik, Joydeep Dutta, Russell Luke, Javier Peña and Stephen Wright.
Registration and more info: https://t.co/PaElodJLpf
email: nsukhorukova@swin.edu.au
The School of Information Technology at Deakin delivers courses in information technology, computer science, data analytics, cyber security and software engineering to provide our graduates with a sound platform for the diverse employment opportunities that will exist in the future.
The Research Fellow, Decision Analytics will be responsible for researching, publishing and contributing to the research project in computational methodologies for complex and uncertain, multi-criteria, multi-objective combinatorial optimization problems.
This is a great opportunity to gain excellent research training and hands-on industry experience through working collaboratively and closely with academic collaborators and industry partners.
https://careers.pageuppeople.com/949/cw/en/job/511749/research-fellow-decision-analytics
The McKenzie Postdoctoral Fellowships Program is a University of Melbourne scheme. The fellowship funds a three year appointment commencing at Level A.6 in the University salary band plus superannuation. Fellows will receive an additional $25,000 to be spent on project costs over the term of their Fellowship.
The EOI deadline is July 5th 2021, and the full application deadline is August 23rd 2021.
Further details:
Friday 9th July
The New South Wales branch of ANZIAM will hold a one-day virtual conference on Friday 9th July. A Zoom link will be sent at a later date.
The conference will run from approximately 10am to 5.30pm (depending upon the number of speakers).
This meeting features the 2020 winner of WIMSIG Maryam Mirzakhani Award, Dr Hoa Bui (Curtin) as the invited speaker: https://www.maintenance.org.au/users/viewuserprofile.action?username=hoa.bui. Title: Optimisation Methods for Maintenance Scheduling in the Mining Industry.
There is no registration fee.
If you would like to give a presentation or are planning on attending please contact Dr Xiaoping Lu (xplu@uow.edu.au) by 30 June, and abstracts/titles of presentations should
be send to Xiaoping by Tuesday 6 July.
Election of Speakers
———————
ECRs and students are strongly encouraged to attend and present at the meeting.
In the fortunate event that we are over-subscribed with speakers, priority will be given to students and ECR, with preference given to NSW ANZIAM members. For established researchers, preference will again be given to NSW ANZIAM members.
Student prize
A prize in the value of $100, will be awarded to the best student presentation.
Organisers
———-
Dr Xiaoping Lu,
Centre for Financial Mathematics,
School of Mathematics and Applied Statistics,
University of Wollongong
A/P Mark Nelson
Centre for Multidisciplinary Mathematical Modelling,
School of Mathematics and Applied Statistics,
University of Wollongong
The Research Fellow is expected to conduct world-class research and provide training for research students working in industrial optimisation as a key appointee in a newly established ARC Training Centre in Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA). The research program involves a focus on model-based and black-box optimisation methodologies of relevance to a broad range of industry partner optimisation challenges. A
multidisciplinary approach is expected, drawing from techniques developed in mathematics, computer science, statistics, engineering, and economics.
For more details, please refer to
http://jobs.unimelb.edu.au/caw/en/job/904801/optima-postdoctoral-research-fellow
Workshop on the Intersections of Computation and Optimisations
MoCaO (Mathematics of Computation and Optimisation) is planning a new workshop for late 2021 which is sponsored by the ANU, UNSW and AMSI.
This workshop intends to bring together researchers from the areas of computation, optimisation, computing sciences and engineering interested in the cross- fertilization of ideas around the following theme:
Optimisation often faces unique issues when there is a need to efficiently compute. On the other hand, computational techniques at times utilise optimisation within their algorithms. Both areas fundamentally need to understand approximation in all its facets which is also fundamental to computation as are the associated notions of convergence. Indeed, recent research has blurred the boundaries between optimisation (continuous and discrete), computation and areas of computing science. The area of machine learning has crept into relevance everywhere. Recently research has turned to its use in computational techniques including the enhancement of optimisation algorithms and the cycle of cross fertilisation of ideas has continued to date.
Workshop Format
We intend to run the workshop in a blended format, involving a face to face component which will be held at the ANU mathematics school in conjunction with a simultaneous\parallel online format to which both group of participants will engage. Some keynotes will present in person (streamed online from ANU) and other will engage totally online in a remote format. We encourage local and international participants to take part in the online workshop. In addition to their keynote presentations, keynotes who will be invited to give a lectorial-discussion session that will promote research questions and engage emerging researchers in these areas.
Keynotes Speakers:
Prof Gerlind Plonka-Hoch (University of Goettingen, Germany)
Prof. Frances Kuo (UNSW)
Prof Stefan Wild (Argonne, USA)
Prof Stephen Wright (Wisconsin, USA)
Prof. Ian Turner (QUT)
Prof. Claudia Sagastizabal (IMECC-Unicamp and CEMEAI, Brazil)
Prof Martin Berggren (Umeå University, Sweden)
Important dates:
Registration Opens: 07/06/2021
Workshop Dates: 22/11/2021 to 25/11/2021
Local Organising Committee
Prof. Andrew Eberhard (RMIT) andy.eberhard@rmit.edu.au
Prof. Stephen Roberts (ANU) stephen.roberts@anu.edu.au
Prof. Markus Hegland (ANU) markus.hegland@anu.edu.au
Dr. Matthew Tam (UniMelb) matthew.tam@unimelb.edu.au
Dr. Nadia Sukhorukova (Swinburne) nsukhorukova@swin.edu.au
Future Announcements and Grants:
We intend to follow up with regular announcements regarding workshop accommodation, details on format and software and funding opportunities for ECR, PHD and female participants. We also wish to draw female participants attention to the possibility of applying for the WIMSIG Cheryl E. Praeger Travel Award (support for attending conferences/visiting collaborators) and/or the WIMSIG Anne Penfold Street Awards (support for careering responsible while attending conferences/visiting collaborators).
The Postdoctoral Fellow will undertake collaborative and self-directed research on an ARC-funded Discovery Project titled “Data-driven multistage robust optimization”. The primary research goals are to make a major contribution to the understanding of optimization in the face of data uncertainty and to develop mathematical principles for broad classes of multi-stage robust optimization problems, to design associated data-driven numerical methods to find solutions to these problems, and to provide an advanced optimization framework to solve a wide range of real-life optimization models of multi-stage technical decision-making under uncertain environments.
For more information, please refer to