Seminar Series on Computational Mathematics

Dear MoCaO members.

We want to inform you about the launch of the Australian Seminar on Computational Mathematics.

You can visit the seminar webpage (main menu, CM Webinar)

where you can find the scheduled talks details and instructions about

1) livestream access to the talk and

2) subscription to the mailing list that will be used to announce new talks.

The inaugural talk will be Tue Feb 09 5pm AEDT, and it will be delivered by Alexandre Ern (Université Paris-Est, CERMICS , ENPC).

PhD Scholarship: Convergence Speed of Optimisation Algorithms

SCHOOL OF MATHEMATICS AND APPLIED STATISTICS (SMAS),
UNIVERSITY OF WOLLONGONG, AUSTRALIA
An exciting PhD scholarship is available in the School of Mathematics and Applied Statistics (SMAS) at the University of Wollongong, South Western Sydney campus, in the area of Optimisation. The title of the project is Determining the Convergence Speed of Derivative-free Optimisation Algorithms. The UOW scholarship is $28,092AUD tax-free per year for
three years full-time. Tuition fees (for up to 4 years) will be waived. The successful applicant will have the opportunity to work with both Australian and international collaborators, and extra funding may be available for conference travel. Applications are invited from domestic and international students who are able to commence PhD studies at the University of Wollongong in 2021.

https://documents.uow.edu.au/content/groups/public/@web/@eis/documents/doc/uow261302.pdf
HOW TO APPLY
If you are interested in applying for this scholarship, please contact Dr Chayne Planiden via email: chayne@uow.edu.au. Applications must include CV detailing previous education experience and academic transcripts. It is expected that the successful applicant will be available to commence this scholarship by 31 October 2021. Applications close 30 November, 2020.

POSTDOCTORAL RESEARCH FELLOW (4 POSITIONS), University of Melbourne

Job no: 0051226

Work type: Fixed Term

Location: Parkville

Division/Faculty: Faculty of Science

Department/School: School of Mathematics and Statistics

Role & Superannuation rate: Academic – Full time – 9.5% super

Salary: Level A: $73,669 – $99,964 p.a (PhD entry level $93,120) or Level B: $105,232 – $124,958 p.. Level of appointment is subject to applicants’ qualifications and experience. 

The School of Mathematics and Statistics at the University of Melbourne has four two-year research positions available for exceptional early career researchers in the mathematical sciences, whose research has the potential to have a significant impact, either in fundamental research or toward practical applications. The School maintains activity in all areas of the mathematical sciences, and the positions can be related to any area.

For more details please refer to

http://jobs.unimelb.edu.au/caw/en/job/903384/postdoctoral-research-fellow-4-positions

ARC PhD Scholarship ($31,885pa): Switching Dynamics Approach for Distributed Global Optimisation

ARC PhD Scholarship ($31,885pa): Switching Dynamics Approach for Distributed Global Optimisation

https://www.rmit.edu.au/students/student-essentials/information-for/research-candidates/enriching-your-candidature/grants-and-scholarships/postgraduate-by-research/switching-dynamics-approach-distributed-global-optimisation

Fast growing big-data in industrial systems makes finding optimal solutions for timely decision making more difficult. This project aims to create a breakthrough switching dynamics approach and new technology to speed up finding optimal solutions. It will develop a distributed switching dynamics based optimisation scheme for global optimisation problems in big-data environments, hence resulting in a practical technology for industry applications (e.g. smart grids).

The specific objectives of this Project are:

1. Establish a switching dynamics approach for global optimisation, forming the foundation to accelerate convergence to search for optimal solutions.

2. Create an intelligent distributed global optimisation scheme with switching dynamics based multi-agent system concepts, which is scalable to big-data optimisation tasks.

This is a project funded by an Australian Research Council (ARC) Discovery Grant for three years (2021-2023), which aims to develop a breakthrough switching dynamics approach and new technology for global optimisation tasks in big-data applications.

The successful applicant will work on this project for the PhD in the School of Science at RMIT University supervised by Prof. Andrew Eberhard and carried out in collaboration with Prof. Xinghuo Yu (Electrical Engineering) at RMIT.

Qualifications

You are required to have a Bachelor degree in a relevant discipline such as Mathematical Sciences or Electrical Engineering with at least 2nd class upper honours or equivalent.  Experience in one or more areas in Nonlinear Dynamical Systems, Discontinuous Control Systems, Optimisation theory and\or Optimisation Algorithms is desirable. The applicant must have a strong background in mathematics.

Application

A CV detailing your qualifications, research experience and achievements, a statement of your suitability to this project, and contact details of two referees are to be emailed to Professor Andrew Eberhard at andy.eberhard@rmit.edu.au.  For further information, please contact Prof. Andrew Eberhard directly.

The Euler International Mathematical Institute in St. Petersburg is seeking postdocs in all areas of Mathematics, Theoretical Computer Science, Mathematical and Theoretical Physics.

Call for Postdocs 2020

The Euler International Mathematical Institute in St. Petersburg is seeking postdocs in all areas of Mathematics, Theoretical Computer Science, Mathematical and Theoretical Physics.

Applicants should send their applications to euler.postdoc@gmail.com

The applications should include:

  • CV,
  • List of publications (including preprints, if necessary),
  • Description of research interests, ideally mentioning possible host or other research contacts in St.Petersburg,
  • Names, affiliations and contacts of 2-3 people willing to send recommendation letters if asked by the committee,
  • Any special requirements wrt the dates, etc.

Basic conditions:

  • Competitive salary of 126,314 RUB per month (taxed at 13% for residents and foreigners), this is double the average salary in St. Petersburg,
  • Housing allowance enough to cover all or most of the rent (in addition to the salary),
  • The institute partially covers travelling expenses to St. Petersburg of up to 300 Euro for the postdocs from Europe and up to 600 Euro for the postdocs outside Europe,
  • The institute has some funds for covering participation in conferences that cannot be covered from other sources,
  • 1 or 2 years extendable for another year,
  • Small teaching load,
  • Flexibility with respect to the starting date, length, specific calendar requirements (such as a leave in the middle),

St. Petersburg is the most beautiful city in the world and has multiple mathematical locations including Steklov Institute of Mathematics http://www.pdmi.ras.ru/pdmi/en/laboratories and the newly created Department of Mathematics and Computer Science in St. Petersburg State University http://math-cs.spbu.ru/en/people/ (the links are provided also as a “menu” of possible hosts).

The preference is given to applications completed before November 30, 2020. Preferable starting date is September 1, 2021.

If you have questions, please do not hesitate to ask them by email.

PhD Scholarship: Convergence Speed of Optimisation Algorithms


SCHOOL OF MATHEMATICS AND APPLIED STATISTICS (SMAS),
UNIVERSITY OF WOLLONGONG, AUSTRALIA


An exciting PhD scholarship is available in the School of Mathematics and Applied Statistics (SMAS) at the University of Wollongong, South Western Sydney campus, in the area of Optimisation. The title of the project is Determining the Convergence Speed of Derivative-free Optimisation Algorithms. The UOW scholarship is $28,092AUD tax-free per year for
three years full-time. Tuition fees (for up to 4 years) will be waived. The successful applicant will have the opportunity to work with both Australian and international collaborators, and extra funding may be available for conference travel. Applications are invited from domestic and international students who are able to commence PhD studies at the University of Wollongong in 2021. Applicants should hold, or be close to completing, an Honours 1 undergraduate degree or a Master’s degree in Applied
Mathematics, Computational Mathematics or a closely related field.

HOW TO APPLY
If you are interested in applying for this scholarship, please contact Dr Chayne Planiden via email: chayne@uow.edu.au.

Applications must include CV detailing previous education experience and academic transcripts. It is expected that the successful applicant will be available to commence this scholarship by 31 October 2021. Applications close 30 November, 2020.
MORE INFORMATION
Dr Chayne Planiden, Lecturer
School of Mathematics & Applied Statistics, University of Wollongong, NSW, Australia
Email: chayne@uow.edu.au

Invitation for Submissions to the Topical Collection “Mathematics of Computation and Optimisation” (MoCaO) in Advances in Computational Mathematics (ACOM)

Objective:
In an effort to promote interaction between researchers in Computational Mathematics and Optimization we plan a collection of articles in ACOM whose topics span both research fields.

The submissions should be done via ACOM submission system:

https://www.springer.com/journal/10444/updates/18256258

Guest Editors:
Jerome Droniou (Monash University, Melbourne, Australia)
Andrew Eberhard (RMIT, Melbourne, Australia)
Guoyin Li (University of New South Wales, Sydney, Australia)
Russell Luke (University of Goettingen, Germany)
Thanh Tran (University of New South Wales, Sydney, Australia)

The board is chaired by Thanh Tran.

Submission deadline: July 31, 2021.

UNSW Seminar: Tiangang Cui (Monash)

Title: Tensorised Rosenblatt Transport for High-Dimensional Stochastic Computation

Speaker: Tiangang Cui (Monash University)

Date: Tue, 07/07/2020 – 11:05am

Venue: Zoom meeting (connection details here)

Abstract: 

Characterising intractable high-dimensional random variables is one of the fundamental challenges in stochastic computation. It has broad applications in statistical physics, machine learning, uncertainty quantification, econometrics, and beyond. The recent surge of transport maps offers a mathematical foundation and new insights for tackling this challenge.

In this talk, we present a functional tensor-train (FTT) based monotonicity-preserving construction of inverse Rosenblatt transport in high dimensions. It characterises intractable random variables via couplings with tractable reference random variables. By integrating our FTT-based approach into a nested approximation framework inspired by deep neural networks, we are able to significantly expand its capability to random variables with complicated nonlinear interactions and concentrated density functions. We demonstrate the efficacy of the FTT-based inverse Rosenblatt transport on a range of applications in statistical learning and uncertainty quantification, including parameter estimation for dynamical systems, PDE-constrained inverse problems, and Bayesian filtering.

This is joint work with Dr. Sergey Dolgov (Bath) and Mr. Yiran Zhao (Monash)

A postdoctoral position in optimisation/OR and/or optimal control (Curtin)

Research Associate/Fellow – Optimisation, Optimal Control or Operations Research

  • Academic
  • Perth, Western Australia
  • Full Time

3 years fixed-term

As a research associate/fellow, you will work as part of an existing research group to advance the school’s research agenda in optimisation, optimal control, and operations research.

For more information please visit:

http://staff.curtin.edu.au/job-vacancies/?ja-job=140126

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