Research Associate - Mathematics and Statistics

UNSW; Milano; In loco; EUR 113.000 - 121.000; Tempo pieno

Descrizione del lavoro

Join a leading university as a Research Associate in Mathematics and Statistics, focusing on innovative high-dimensional approximation research. Collaborate with top academics in an enriching environment while contributing to impactful research that influences real-world applications.

Competenze

• PhD in Mathematics, preferably computational mathematics.
• Demonstrated ability to conduct independent research.
• Strong computer programming experience.

Mansioni

• Conduct research on High Dimensional Approximation and Machine Learning.
• Write scientific papers for international journals.
• Assist with research coordination and proposal submissions.

Conoscenze

Independent research

Interpersonal skills

Team collaboration

Communication

Programming (Matlab, C++, Python)

Formazione

PhD in Mathematics or related area

Descrizione del lavoro

Research Associate - Mathematics and Statistics

Join to apply for the Research Associate - Mathematics and Statistics role at UNSW

Research Associate - Mathematics and Statistics

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Join to apply for the Research Associate - Mathematics and Statistics role at UNSW

• 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
  
  
  

This Job is based in Australia

• 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.

The School of Mathematics and Statistics currently has more than eighty continuing academic staff and more than thirty research staff as well as visiting academics. UNSW is the only university in Australia to be ranked in the top 100 in the world in mathematics and statistics by CWTS Leiden, US News and QS. The School embodies a broad range of research interests in the areas of applied and pure mathematics, and statistics.

The Research Associate will undertake collaborative and self-directed research on an ARC-funded Discovery Project titled “High Dimensional Approximation, Learning, and Uncertainty”. The aim of the project is to devise and apply innovative schemes for high-dimensional approximation. These schemes will be of proven reliability and accuracy, able to handle variables or uncertain parameters numbering in the hundreds or more, fast in execution, and tailored to specific applications.

THIS ROLE IS BASED IN SYDNEY, AUSTRALIA.

About The Role

• Level A - $113K - $121K plus 17% Superannuation and annual leave loading
• Fixed Term – 2 years
• Full-time (35 hours per week)
  
  
  

The role reports to Professor Frances Kuo and Professor Ian Sloan and has no direct reports.

Specific Responsibilities For This Role Include

• Conduct research in the area of High Dimensional Approximation, Uncertainty Quantification, Deep Learning, and Quasi-Monte Carlo Methods independently and as part of a team, including leading some areas of the project where the opportunity arises and where appropriate.
• Contribute to the writing of scientific papers and reports for international journals and progress reporting to other researchers and industry partners.
• Assist with the coordination of research activities and actively contribute to research outputs to meet project milestones.
• Contribute to the preparation of research proposal submissions to funding bodies and actively seek collaboration with industry partners as appropriate.
• Participate in and/or present at conferences and/or workshops relevant to the project as required.
• Joint supervision of honours and HDR students.
• Align with and actively demonstrate the Code of Conduct and Values
• Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on the health and safety of yourself or others.
  
  
  

About The Successful Applicant

(Selection Criteria)

To Be Successful In This Role You Will Have

• A PhD in Mathematics, preferably in computational mathematics or related area.
• Demonstrated ability to conduct independent research with limited supervision.
• Strong interpersonal skills with demonstrated ability to communicate and interact with a diverse range of stakeholders and students.
• Demonstrated knowledge in Quasi-Monte Carlo methods and/or finite element analysis and/or machine learning is highly desirable.
• Strong computer programming experience, preferably with Matlab, C++, or Python.
• Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.
• Evidence of highly developed interpersonal skills.
• Demonstrated ability to communicate and interact with a diverse range of stakeholders and students.
• An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines.
• Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training.
  
  
  

You should systematically address the selection criteria listed within the position description in your application.

For informal queries, please see the below contact details.

Otherwise, please apply online - applications will not be accepted if sent directly to the contact listed.

Contact:

Frances Kuo

E: [e-mail]

Applications close: August 8th, 2025

Find Out More About Working At UNSW At Www.unsw.edu.au

UNSW is committed to equity diversity and inclusion. Applications from women, people of culturally and linguistically diverse backgrounds, those living with disabilities, members of the LGBTIQ+ community; and people of Aboriginal and Torres Strait Islander descent, are encouraged. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research

• Industries

  Higher Education and Research Services

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