Research Associate in Spatio-Temporal ML

Research Associate in Spatio-Temporal ML

Job no: 528076

Work type: full time

Location: Sydney, NSW

Categories: Post Doctoral Research Associate

The Opportunity

The School of Computer Science and Engineering has an opportunity for a Research Associate. In this role you will conduct research in the field of Machine Learning, Fairness and Bias in AI, and Spatio-Temporal Forecasting for a collaborative project between researchers in the USA and Australia, that is funded by the U.S. NSF and CSIRO. The project, led by universities in both countries, aims to reduce bias in AI models used for predicting disease spread to improve pandemic response. Researchers will study how biased data affects AI models and explore fairness metrics to incorporate into AI optimization to mitigate bias.

This position will give you the opportunity to advance your scholarly research and professional endeavours both nationally and internationally. Your contributions will include publishing scientific papers and reports in international journals, actively participating in conferences and workshops, and collaborating closely with industry partners.

This role reports to Professor Flora Salim and has no direct reports.

Salary: Level A, Step 6 - AUD$110,059 per annum + 17% superannuation

Full time

Fixed-term contract: 18 months

Location: Kensington – Sydney, Australia

About UNSW

UNSW isn’t like other places you’ve worked. Yes, we’re a large organisation with a diverse and talented community; a community doing extraordinary things. But what makes us different isn’t only what we do, it’s how we do it. Together, we are driven to be thoughtful, practical, and purposeful in all we do. If you want a career where you can thrive, be challenged and do meaningful work, you’re in the right place.

The School of Computer Science and Engineering is one of the largest and most prestigious schools of computing in Australia. It offers undergraduate programmes in Software Engineering, Computer Engineering, Computer Science, and Bioinformatics, as well as a number of combined degrees with other disciplines. Our research and teaching staff are world leading and world building as they advance knowledge and learning.

Skills and Experience

• A PhD in a related discipline, and/or strong research experience in one or more of the following:
• Spatio-temporal modelling / data mining
• Deep learning, self-supervised learning, data-efficient learning
• Imbalanced learning, ML bias
• Dealing with highly sparse and biased data
• 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 top-tier publications and conference presentations relative to opportunity, particularly in highly prestigious Q1 journals and conferences in AI, machine learning, and data mining, statistical ML, and/or spatial epidemiology research.
• Strong coding capabilities in running ML and data analytics experiments.
• Strong interests in the digital, technical, and societal aspects of public health research domain.
• 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.

Additional details about the specific responsibilities for this position can be found in the position description. This is available via JOBS@UNSW.

To Apply:

Please click the apply now button and submit your CV, Cover Letter and Responses to the Skills and Experience. You should systematically address the Skills and Experience listed within the position description in your application.

Applicants must have working rights in Australia and be able to be on site in Kensington regularly.

Please note applications will not be accepted if sent to the contact listed below.

Contact:

Eugene Aves – Talent Acquisition Consultant

E: eugene.aves@unsw.edu.au

Applications close: 11:55 pm (Sydney time) on Sunday 27 October 2024

UNSW is committed to evolving a culture that embraces equity and supports a diverse and inclusive community where everyone can participate fairly, in a safe and respectful environment. We welcome candidates from all backgrounds and encourage applications from people of diverse gender, sexual orientation, cultural and linguistic backgrounds, Aboriginal and Torres Strait Islander background, people with disability and those with caring and family responsibilities. 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.

Position Description

Advertised: 04 Oct 2024 AUS Eastern Standard Time

Applications close: 27 Oct 2024 AUS Eastern Daylight Time