Mathematics and Statistics, University of New South Wales

648 11756Position ID: UNSW-RA [#11756, 61147]
Position Title: Postdoctoral Fellow in Computational Mathematics
Position Type: Postdoctoral
Position Location: Sydney, NSW 2031, Australia [map]
Subject Area: Computational Mathematics
Application Deadline: 2018/03/31 (posted 2018/02/27, listed until 2018/08/27)
Position Description:    

*** The account for Mathematics and Statistics, University of New South Wales has expired. ***

Postdoctoral Fellow in Computational Mathematics  
Faculty of Science 
School of Mathematics & Statistics 
 Ref 61147 

  • One of Australia’s leading research & teaching universities 
  • Vibrant campus life with a strong sense of community & inclusion 
  • Enjoy a career that makes a difference by collaborating & learning from the best 

At UNSW, we pride ourselves on being a workplace where the best people come to do their best work. 

Applications are sought for a TWO Postdoctoral Fellow positions in Computational Mathematics in the School of Mathematics and Statistics, UNSW Sydney. 

About the roles
  • A$89K – A$96K per year (plus up to 17% superannuation and leave loading). 
  • Full-time position for a fixed term of up to 2 years. 
  • No teaching duty is required 
These positions are funded by Australian Research Council Discovery Project Grants. 

 About the projects:  

The core of Dr. Q Thong Le Gia and Professor Ian Sloan’s joint project is to advance uncertainty quantification theory and computational methods for problems involve uncertainty on spheres and spherical shells. 

A/Professor Frances Kuo and Professor Ian Sloan’s joint project is titled “Towards a science of high dimensional computation”. This project aims to establish scientifically precise methods for high dimensional problems – methods that are mathematically rigorous, empirically tested, and carefully tailored to specific modern applications across physics, environment, and finance. 

The successful applicant will play a leading role within one of these research projects and is expected to publish in leading international journals. 

About you: 

To be successful in this role, you will have: 

  • For the Le Gia and Sloan project: PhD in Mathematics, or be close to completing one, in computational mathematics or stochastic analysis. 
  • For the Kuo and Sloan project: PhD in Mathematics, or be close to completing one, in computational mathematics, or computational or statistical physics, or Bayesian analysis. Knowledge in quasi-Monte Carlo methods and/or finite element analysis is highly desirable, though not essential 
  • Strong research and publication track record (relative to career opportunity) 
  • Demonstrated high level analytical and problem-solving skills 

Applicants may be required to undergo pre-employment checks prior to appointment to this role. Please address the selection criteria listed within the position descriptions in your application. Please indicate whether you want to be considered for both positions, or have a preference for one or the other. Please note that successful candidates who wish to be considered for both roles will only need to attend one interview. 

Please apply online - applications will not be accepted if sent directly to the contacts listed. 

Contact: 
 
Prof Ian Sloan i.sloan@unsw.edu.au 

For specific queries on either project please contact 

 Dr Q. Thong Le Gia qlegia@unsw.edu.au 

 A/Prof Frances Kuo f.kuo@unsw.edu.au 

Applications close: 31st March 2018 
For full details of this position and application procedure, click here.  Alternatively, please go to http://www.jobs.unsw.edu.au/ and search for keyword "computational mathematics"

This employer is not accepting applications for this position through Mathjobs.Org. Please see the job description above on how to apply.
Contact: Gary Froyland
Email:
Postal Mail:
School of Mathematics and Statistics
University of New South Wales
Sydney NSW 2031
Australia
Web Page: http://www.maths.unsw.edu.au/

© 2018 MathJobs.Org, American Mathematical Society. All Rights Reserved.