• Full time 2 year fixed term, located on the Camperdown Campus at the School of Mathematics and Statistics
• Opportunity to make valuable contributions to research at the interface between dynamical systems and machine learning
• Base Salary Level A $97,043 p.a. - $100,717 p.a. + 17% superannuation

About the opportunity

We are seeking to appoint a Postdoctoral Research Associate to work on a project entitled “A dynamical systems theory approach to machine learning”. The successful candidate will work under the supervision of Professor Georg Gottwald on developing, understanding and applying machine learning techniques using tools from dynamical systems theory. This project has recently been funded by the Australian Research Council.

Forecasting the future state of a high-dimensional complex multi-scale system is a challenge we face in areas ranging from climate science to epidemiology. Even when basic physical mechanisms have been identified, the actual evolution equations are often unknown. This project will develop a computationally cheap machine learning framework for forecasting. We will develop mathematical theory underpinning the novel methodology, as well as applying it to the perennial problem of subgrid-scale parametrisation in climate modelling. Furthermore, we will apply dynamical systems theory to understand existing machine learning algorithms.

Your key responsibilities will be to:

• undertake research at the interface between dynamical systems and machine learning
• publish research papers
• demonstrate research excellence.

The School of Mathematics and Statistics of the University of Sydney is one of the largest in Australia. It has more than 89 academic staff to supervise research and teaching 74 postgraduate students and 925 equivalent full-time student-load undergraduate students.

To learn more about the School of Mathematics and Statistics click here

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Postdoctoral Research Associate who has:

• a PhD (or near completion) in mathematics or a relevant area
• relevant expertise in dynamical systems and machine learning desired
• demonstrated ability to conduct research/scholarly activities under limited supervision
• the ability and a willingness to collaborate in multidisciplinary teams to contribute to long-term research goals
• a strong track record of publishing their research
• excellent communication (written and verbal), organisational and problem-solving skills with attention to detail
• high level interpersonal skills, including the ability to work collaboratively with colleagues
• a demonstrated ability to complete work in timely fashion and to write up results for publication.

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

Closing date for applications 

11.59pm, 22 February 2023

CLICK HERE TO APPLY: 

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