Research Associate - Machine Learning (Environmental Technologies)
Research Associate - Machine Learning (Environmental Technologies)

Research Associate - Machine Learning (Environmental Technologies)

Full-Time 80000 - 90000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop advanced machine learning models to optimise water treatment and environmental management.
  • Company: Join UNSW, a leading institution focused on impactful research and innovation.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Why this job: Make a real difference in environmental technologies while collaborating with industry experts.
  • Qualifications: PhD or equivalent experience in relevant fields, strong coding skills, and machine learning expertise.
  • Other info: Dynamic team environment with a commitment to diversity and inclusion.

The predicted salary is between 80000 - 90000 £ per year.

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.

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.

Skills & Experience:

  • 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.

Pre‑Employment Checks:

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:

  • 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.

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 work on site in Kensington.

Contact:

For role‑specific inquiries, please contact Prof David Waite: d.waite@unsw.edu.au

For questions regarding the recruitment process, please contact Eugene Aves (Talent Acquisition Partner): eugene.aves@unsw.edu.au

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.

Research Associate - Machine Learning (Environmental Technologies) employer: UNSW

UNSW offers a dynamic and inclusive work environment where innovation meets purpose, particularly in the field of environmental technologies. As a Research Associate, you will have the opportunity to engage in cutting-edge research that directly impacts water treatment processes and environmental management, all while collaborating with a diverse team of experts. With a strong commitment to employee growth, competitive salaries, and flexible working options, UNSW is dedicated to fostering a culture where you can thrive and make a meaningful contribution to society.
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Contact Detail:

UNSW Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Research Associate - Machine Learning (Environmental Technologies)

✨Tip Number 1

Network like a pro! Reach out to your connections in the environmental tech space, especially those who might know someone at UNSW. A friendly chat can sometimes lead to opportunities that aren’t even advertised.

✨Tip Number 2

Show off your skills! If you’ve got a portfolio of machine learning projects or relevant research, make sure to highlight them in conversations. Bring them up during interviews or networking events to demonstrate your expertise.

✨Tip Number 3

Prepare for the interview by understanding UNSW’s mission and values. Tailor your responses to show how your goals align with theirs. This will help you stand out as a candidate who truly fits into their culture.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at UNSW and contributing to their innovative projects.

We think you need these skills to ace Research Associate - Machine Learning (Environmental Technologies)

Machine Learning
Python
JavaScript
C
UI Design
Prototyping
Usability Testing
Digital Twin Development
Research Skills
Technical Report Writing
Water Treatment Technologies
Environmental Processes
Interpersonal Skills
Communication Skills
Project Management

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to highlight your skills in machine learning and environmental technologies. We want to see how your experience aligns with the role, so don’t be shy about showcasing relevant projects or research!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about this role and how your background makes you a perfect fit. Remember, we love seeing enthusiasm for both the research and the impact it can have on the environment.

Address the Skills and Experience: When responding to the Skills and Experience section, be systematic. We want to see clear examples of how you meet each requirement. This helps us understand your qualifications better and shows that you’ve done your homework!

Apply Through Our Website: Don’t forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, it keeps everything organised on our end, making it easier for us to review your materials.

How to prepare for a job interview at UNSW

✨Know Your Machine Learning Stuff

Make sure you brush up on your machine learning algorithms and coding skills, especially in Python, JavaScript, and C. Be ready to discuss specific projects where you've applied these skills, as this will show your practical experience and understanding of the field.

✨Understand Water Treatment Technologies

Familiarise yourself with the latest advancements in water treatment technologies and environmental processes. Being able to discuss how your research can contribute to optimising these processes will demonstrate your commitment to the role and the impact you can make.

✨Show Off Your Collaboration Skills

Since this role involves working with multidisciplinary teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight your interpersonal skills and how you’ve effectively communicated with diverse stakeholders.

✨Prepare for the Mandarin Requirement

If you’re proficient in Mandarin, think about how you can leverage this skill in your role. Be ready to discuss any relevant experiences where you've used Mandarin in a professional context, especially in liaising with industry partners.

Research Associate - Machine Learning (Environmental Technologies)
UNSW
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  • Research Associate - Machine Learning (Environmental Technologies)

    Full-Time
    80000 - 90000 £ / year (est.)
  • U

    UNSW

    1000-5000
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