Research Associate - Mathematics and Statistics

• 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 sixty 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 each of the four ranking bodies: CWTS Leiden, ARWU, USNews, QS.

The School embodies a broad range of research interests in the areas of applied mathematics, pure mathematics, statistics, and data science. It has particular research strengths in Algebra, Analysis, Bayesian and Monte Carlo Methods, Biomathematics, Biostatistics and Ecology, Combinatorics, Computational Mathematics, Data Science, Dynamical Systems and Integrability, Finance and Risk Analysis, Fractional Calculus, Functional and Harmonic Analysis, Geometry and Mathematical Physics, Nonparametric Statistics, Number Theory, Ocean and Atmospheric Sciences, Optimisation, Point Processes, Stochastic Analysis, and Stochastic Modelling.

The Research Associate is expected to contribute towards the research effort of UNSW and to develop their research expertise through the pursuit of defined projects relevant to their particular field of research, specifically to an ARC-funded Discovery Project titled “Inference for Hawkes processes with challenging data.”

The primary research goals are to develop novel theories and methodologies of statistical inference for a class of stochastic point processes with incomplete data and to apply point process theory and methodologies to solve problems arising in other disciplines, such as environmental sciences, finance and economics, neuroscience, criminology, media study and social sciences. This role will be based in the School of Mathematics and Statistics at the University of New South Wales.

About the role

• $106K - $113K plus 17% Superannuation and annual leave loading
• Fixed term – 18 months
• Full time (35 hours)

The role of Research Associate reports to Associate Professor Feng Chen with a dotted line to Dr Tom Stindl and will work closely with Emeritus Professor William Dunsmuir and Prof Jiancang Zhuang (Institute of Statistical Mathematics and the University of Tokyo). This role has no direct reports.

Specific responsibilities for this role include:

• Contribute independently or as a team member in collaborative research with a focus to enhance the quality of research outcomes in the Point Process group at UNSW Sydney.
• Undertake specific research project/s under the guidance of a research leader(s) and contribute to development of research activities.
• Undertake discipline-appropriate research activities, e.g. surveys, literature reviews, data gathering and/or recording of results using appropriate research methods.
• Participate in and/or present at conferences and/or workshops relevant to the project as required.
• Assist with the supervision of research students in the research area where required.
• Develop statistical inference theory and methodologies for the Hawkes process and related point process models with incomplete data.
• Implement newly developed statistical inference methodologies in commonly used languages for statistics and data science.
• Solve applied questions arising in interdisciplinary studies.
• Collaborate on publications in internationally refereed journals in statistics and other relevant disciplines.
• Satisfactory conduct of administrative and other duties allocated by the supervisor(s).
• 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.

Selection Criteria

To be successful in this role you will have:

• A PhD in Statistics with research exposure to Stochastic Processes (ideally Point Processes).
• Knowledge of statistical computing techniques.
• Strong computer programming skills, preferably in R, Julia, C++, or Python.
• Strong research track record (relative to opportunity) in Statistics, as evidenced by publications in international peer-reviewed journals.
• Proven commitment to proactively keeping up to date with discipline knowledge and developments.
• Demonstrated ability to undertake high quality academic research and conduct independent research with limited supervision.
• Demonstrated track record of publications and conference presentations relative to opportunity.
• 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:
Feng Chen
E: [email protected]

Applications close: July 11^th, 2024

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).