Postdoctoral Research Fellow in Auditory Signal Processing

Macquarie University
September 29, 2024
Contact:N/A
Offerd Salary:$106,089 - $113,697
Location:N/A
Working address:N/A
Contract Type:fixed term for 3 yea
Working Time:Full time
Working type:N/A
Ref info:N/A
PRIMARY DETAIL

Seeking a postdoctoral fellow to lead the development of a low-cost hearing screening device, funded by the Cochlear-Macquarie University Joint Fund. This position offers a unique opportunity to conduct impactful research alongside a multidisciplinary team of hearing scientists, signal processing experts, and mathematicians, all focused on optimizing this innovative screening tool with the potential to detect hearing loss early.

  • Salary Package: From $106,089 - $113,697 (Level A, Step 6 to Step 8), plus 17% employer superannuation and annual leave loading.

  • Type: Full-time, fixed term for 3 years.

  • Location: Macquarie University, Wallumattagal Campus (North Ryde).

  • The Role:

  • Collaborate with leading researchers in hearing science, Cochlear, and mathematicians.

  • Access to an active Early Career Researcher support network and professional development opportunities.

  • Work in state-of-the-art research facilities.

  • We are seeking a motivated Postdoctoral Research Fellow with a background in signal processing and machine learning. The successful candidate will support our research group in developing the next generation of low-cost hearing screening devices.

    In countries like Australia, hearing screening is performed on every newborn to detect hearing loss. However, the current method is costly and not feasible for middle- and low-income countries. Our team is enhancing existing technology using a patented approach to create an affordable solution that could surpass the current gold standard.

    Reporting to Dr. Sriram Boothalingam (Linguistics, MQ and National Acoustic Laboratories), and collaborating with colleagues from the School of Mathematical and Physical Sciences (Profs Benoit Liquet-Weiland and Georgy Sofronov, and Dr. Thomas Fung), as well as industry partner Dr. Zach Smith (Cochlear), you will contribute to the development of signal processing and machine learning-based methods to optimize the screening test.

    This role offers significant research, networking, and mentoring opportunities within a highly experienced and supportive research environment. You will also contribute to other funded projects and help towards implementation of the developed software in hardware devices. The position also provides opportunities to work with several PhD, Masters, and undergraduate students.

    About You: You will hold a PhD in signal processing, machine learning, or a related field such as neuroscience, with substantial experience in signal processing and machine learning. The ideal candidate will be an effective communicator, enjoy working independently and as part of a team, and have a keen eye for detail, ensuring high accuracy and data quality. You will also possess advanced programming skills.

    Skills and Qualifications:

  • PhD in Engineering, Signal Processing, Machine Learning, or Neuroscience with experience applying signal processing and machine learning.

  • Demonstrated ability to plan and conduct experiments and solve problems in research.

  • Strong programming background.

  • Proven contributions to research data analysis, report writing, and publishing manuscripts.

  • Ability to work collaboratively with a diverse team, including faculty administrators, lab staff, and students.

  • Excellent organizational skills, with a track record of independent and team-based work.

  • About Us: This project is funded jointly by Macquarie University and Cochlear for a period of three years. The research will take place at the Australian Hearing Hub, a world-class facility for hearing research that includes an anechoic chamber, EEG, MEG, and acoustic measurement labs. We are part of the Macquarie University Hearing Research Centre, which provides outstanding development options, including the active Early Career Researcher network ("EnCouRage").

    Macquarie University has been committed to solving real-world challenges since its foundation 60 years ago. Over time, we have become a hub for a vibrant and global community.

    To Apply:

    Please apply online by submitting your CV (including 2-3 referees) and a cover letter addressing the selection criteria.

    Essential Selection Criteria:

  • PhD in Engineering, Signal Processing, Machine Learning, or Neuroscience with significant experience in these areas.

  • Strong research skills, including planning and conducting experiments.

  • Demonstrated experience in programming and signal processing.

  • Contributions to research data analysis, drafting reports, and publishing manuscripts.

  • Ability to work effectively in a team and independently.

  • Strong organizational skills and attention to detail.

  • Please note this position is only open to Australian citizens, permanent residents and those currently residing in Australia with complete working rights.

    Specific Role Enquiries: Dr. Sriram Boothalingam, via [email protected]

    General Enquiries: Shubha Moorthy, HR Officer, via [email protected]

    Applications Close : Sunday, 29 September 2024

    If you're already part of the Macquarie Group (MQ University, U@MQ, MQ Health, MGSM), you'll need to apply through your employee Workday account. To apply for this job: Login to Workday and go to the Careers App > Find Jobs.

    Applications Close:

    29/09/2024 11:59 PM

    Diversity and Inclusion

    Innovation and ingenuity thrive at Macquarie University when diversity, equity and inclusion take centre stage. At the University, we embrace a culture where diversity of background, experience and perspective are fundamental to our success.

    We do not discriminate on gender identity, age, culture, disability, sexuality, Indigeneity, family and caring responsibilities or religion. See our journey towards leadership in Equity, Diversity and Inclusion in Higher Education.

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