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Research Associate

Apply now Job no: 501316
Work type: Full-time
Location: Sydney, NSW
Categories: Post doctoral research fellow

  • 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.

This position is fully funded by the Australian Research Council’s Centre of Excellence for Climate Extremes (CLEX) and the Research Associate will contribute to and benefit from being a part of the CLEX community. The Centre’s research agenda encompasses interconnected research programs focused on Weather and Climate Interactions, Drought, Attribution and Risk, Ocean Extremes and Coupled Modelling. CLEX is a major seven-year initiative funded by the Australian Research Council. The Centre is led by UNSW Sydney and partners with Monash, The University of Melbourne, The Australian National University and The University of Tasmania alongside a suite of national and international partner organisations. Climate extremes are the confluence of high impact weather and climate variability. The Centre works to improve our understanding of the processes that trigger or enhance extremes and build this understanding into our modelling systems. The improved predictions of climate extremes will help Australia cope with extremes now and in the future.

The Research Associate will contribute to collaborative research improving the representation of climate extremes simulated by coarse-scale climate models. Machine learning techniques will be used to establish a statistical characterisation of extreme events in high resolution simulations using coarse-scale simulation variables as predictors.

This position sits within the CLEX Attribution and Risk research team and will collaborate with senior and postdoctoral researchers in that team and other CLEX programs. The position will also contribute to the CLEX atmospheric modelling team. The ARC Centre of Excellence for Climate Extremes provides a supportive and enriching workplace for its staff and students through its strong commitment to equity, diversity and inclusion and wellbeing initiatives. The ARC Centre of Excellence will also support the successful candidate in how best to engage beyond academia.


About the role

  • $98K - $105K plus 17% Superannuation and annual leave loading
  • Fixed Term – 3 years
  • Full time (35 hours per week)

The Research Associate will report to Associate Professor Gabriel Abramowitz and has no direct reports.

Specific responsibilities for this role include: 

  • Conduct research into the statistical representation of sub-grid scale variability within coarse resolution climate models, including extreme event characterisation and investigation of appropriate machine learning approaches.
  • Work as a team with other researchers in the Attribution & Risk program using machine learning approaches for related problems.
  • Develop an understanding of the strengths and weaknesses of different machine learning techniques and aid others in their application.
  • Maintain a strong focus on communicating research findings by publishing in highly ranked journals and presenting to peers at local, national and global conferences.
  • Work collaboratively with other researchers among CLEX universities and partner organisations.
  • With the support of the Centre’s Knowledge Brokerage Team, the successful candidate will communicate relevant aspects of the research undertaken to stakeholders outside academia (e.g. through briefing notes, briefings to government, presentations at industry conferences, etc).
  • Contribute to the collegiate life of CLEX such as supporting PhD supervision, committee membership, leading workshops, etc.
  • Align with and actively demonstrate the UNSW Values in Action: Our Behaviours and the UNSW Code of Conduct.
  • 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

To be successful in this role you will have:
(Selection Criteria)

  • PhD in physical climate science, climate modelling, machine learning or relevant statistics applications.
  • Demonstrated ability to carry out scientific research independently and as part of a collaborative team.
  • Strong research and publication track record (relative to opportunity) in an area listed in the position summary.
  • High level analytical and problem-solving skills.
  • Excellent verbal and written communication skills.
  • Demonstrated programming skills in a Unix/Linux environment (E.g. Fortran, Python, R).
  • Willingness to engage with stakeholders outside of academia (e.g. Government agencies, private businesses, NGOs, schools).
  • 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.

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

Contact:
Gabriel Abramowitz
E: gabriel@unsw.edu.au

Applications close: March 28th, 2021


Find out more about working at UNSW at www.unsw.edu.au

UNSW aspires to be the exemplar Australian university and employer of choice for people from diverse backgrounds. UNSW aims to ensure equality in recruitment, development, retention and promotion of staff and that no-one is disadvantaged on the basis of their gender, cultural background, disability, sexual orientation or identity or Indigenous heritage. We encourage everyone who meets the selection criteria to apply.

UNSW partners with Australia’s leading diversity organisations, networks, and campaigns. Please refer to UNSW’s diversity offerings for further information on our flexible work and leave options, and support for carers (childcare, parent rooms, parental leave).

 

Position Description

Advertised: AUS Eastern Daylight Time
Applications close: AUS Eastern Daylight Time

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