Research Associate - Machine Learning (Environmental Technologies)

The School of Civil and Environmental Engineering at UNSW is looking for a motivated Research Associate with skills in Machine Learning to join our team. You will contribute to UNSW’s research efforts by developing advanced machine learning models and software tools aimed at optimizing water treatment processes and facilitating environmental management. You will be expected to combine fundamental research with applied development, supporting industry-funded projects to reduce operational costs and carbon footprint in water treatment and aid in water and air-related environmental management. You will work collaboratively with academic and industry partners, focusing on innovative AI-based solutions integrated with mechanistic models, and will actively disseminate research outcomes through publications and conference presentations.

This role reports to Scientia Professor David Waite and has no direct reports.

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• Salary: Academic Level A, Step 6 or higher (depending on skills and experience): $118,467 to $126,711 per annum + 17% superannuation + annual leave loading
  
• Full time (though consideration will be given to part‑time employment)
  
• Fixed term – 12 months with possible extension
  
• Location: Kensington – Sydney, Australia
  
• Proficiency in Mandarin, both spoken and written, is required for this role
  

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 Civil and Environmental Engineering is in the Faculty of Engineering that has over 3,300 students and an operating budget of over $23 million. The School has 48 full time academic staff, 30 professional and technical staff and 80 research only appointments. The School’s mission is to develop well‑educated graduates with the essential skills, attributes and knowledge that will enable them to practice as professional civil or environmental engineers; and to conduct research and development of international distinction to meet the needs of the discipline, industry and society. For further information about the School, please visit http://www.civeng.unsw.edu.au/.

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• PhD in a relevant discipline or equivalent experience.
  
• Demonstrated ability to undertake high‑quality academic research and conduct independent research with limited supervision.
  
• Strong coding skills in languages such as Python, JavaScript, and C.
  
• Experience in developing machine learning algorithms and front‑end web applications (UI design, prototyping, usability testing).
  
• Experience in digital twin development and application desirable.
  
• Proven research, analysis, and technical report writing skills.
  
• Ability to assimilate knowledge of water treatment technologies and environmental processes and mechanistic aspects of these technologies and processes.
  
• Outstanding interpersonal and communication skills in English (Mandarin proficiency desirable for industry liaison).
  
• Demonstrated ability to work collaboratively in multidisciplinary teams.
  
• Knowledge of water treatment technologies and environmental processes preferred.
  
• Project management experience in large‑scale industry projects desirable.
  
• 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.
  

Aligned with UNSW’s focus on cultivating a workplace defined by safety, ethical conduct, and strong integrity preferred candidates will be required to participate in a combination of pre‑employment checks relevant to the role they have applied for.

These pre‑employment checks may include a combination of some of the following checks:

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• National and International Criminal history checks
  
• Entitlement to work and ID checks
  
• Working With Children Checks
  
• Completion of a Gender‑Based Violence Prevention Declaration
  
• Verification of relevant qualifications
  
• Verification of relevant professional membership
  
• Employment history and reference checks
  
• Financial responsibility assessments/checks.
  
• Medical Checks and Assessments
  

Compliance with the necessary combination of these checks is a condition of employment at UNSW.

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 work on site in Kensington.

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

For role‑specific inquiries, please contact Prof David Waite:

For questions regarding the recruitment process, please contact Eugene Aves (Talent Acquisition Partner):

Applications close: 11:55 pm (Sydney time) on Sunday 8th February 2026.

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.