About the National Acoustic Laboratories (NAL)

NAL is a world leader in hearing research and evidence-based innovation to improve hearing health and transform the lives of people with hearing difficulties. NAL collaborates with organisations around the world to innovate on novel solutions to hearing health services and technology, conduct sophisticated validation trials on treatment benefit, and provide insight into the needs of people with hearing loss and clinicians who treat them. NAL’s research findings are published in leading peer-reviewed journals and its inventions are used worldwide.

About the role

This position offers the opportunity to contribute to pioneering work in hearing health applying machine learning to create impactful solutions. Your work will span from creating groundbreaking innovations to applying advanced data analytics to extract valuable insights from our clinical data warehouse.

This role is pivotal in our mission to improve the lives of people with hearing loss through data-driven innovation. Here’s how you’ll do it:

• – Conduct comprehensive data analyses to extract actionable insights from clinical and audiological data sets.
• – Machine Learning Model Development: Design and develop advanced machine learning models to analyse audiological data and improve diagnostic accuracy for hearing loss.
• – Conduct and manage research studies, working under the guidance of senior researchers and providing updates to relevant stakeholders.
• – Develop Innovative Solutions: Prototype and test new algorithms, approaches and/or automated pipelines for screening and diagnostic tools. Collaborate with audiologists and end users to understand clinical needs and integrate their feedback into the development of solutions.
• – Collaborate on Multidisciplinary Projects: Work alongside other technical and clinical experts to integrate machine learning solutions into broader research and product development initiatives.
• – Stay updated with the latest advancements in machine learning, hearing science and audiology, continuously enhancing skills and knowledge in this area.

What you’ll bring

We believe the successful candidate will have a strong background in machine learning, data analytics, and research:

• – Bachelor’s degree in physics, engineering, computer science, data science, or related discipline.
• – Master’s degree or PhD desirable.
• – Three-years’ research or industry experience
• – Excellent Python skills
• – Strong foundation in machine learning algorithms and principles
• – Experience in developing, training, and deploying machine learning models
• – Expertise in natural language processing or large-language models
• – Proficiency in Matlab or R desirable
• – Excellent ability to understand and synthesise the literature in specific topics
• – Experience in data analysis
• – Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) desirable
• – Experience in conducting research and managing projects
• – Track record of peer-reviewed publications and/or independent or collaborative research desirable
• – Expertise in audio signal processing or acoustics desirable

Why work for NAL? 

At NAL, our mission is to lead the world in hearing research and evidence-based innovation to improve hearing health and transform the lives of people with hearing difficulties. A career with us is rewarding because you are helping to positively impact people’s lives and improve Australia’s hearing health.

The National Acoustic Laboratories is an Equal Opportunity Employer operating under Department of Human Services. Aboriginal & Torres Strait Islander peoples are encouraged to apply.

Let’s create the gold standard of hearing care

We will require the successful candidate to be willing to have a Police Check conducted (we pay), a current driver’s licence and must have rights to work in Australia. NAL is an Equal Opportunity Employer and embraced diversity, equity and inclusion. We are passionate about building a diverse and inclusive culture from within. We encourage Aboriginal and Torres Strait Islander peoples and applicants from different cultures who are bilingual to apply. We are committed to facilitating a barrier-free recruitment process and work environment. If you require any accommodations, we welcome you to let us know so we can work with you to participate fully in our recruitment experience.