The Early Mental Potential & Wellbeing Research Centre's mission is to maximise every child's mental and emotional capital by uplifting neurodevelopmental trajectories during early sensitive periods through interdisciplinary discovery science and translational technologies.

Toward this aim, we engage in 3 major activities and thrusts:

1) Core Discovery Research, Empowering Science: Basic neuroscience research and advanced computational models to understand individual neurocognitive potential, developmental trajectories, and risk and resilience factors;

2) Translation to Clinic & Pedagogy, Empowering Practitioners: Developing precision assessment and intervention tools to optimise parent-child social and mental health within clinical, education and community settings;

3) Translation to Real-World Technologies, Empowering Families: Creating scalable solutions and real-world technologies for parents to enhance their child's mental and cognitive wellbeing at home.

We are seeking a Research Engineer (Audio AI Engineer) to design and implement advanced audio and machine learning models to enhance audio quality in our innovative projects. The postholder will be responsible for developing and optimizing algorithms for audio processing, contributing to both audio research and software development.The postholder will be working closely with PI - Professor Victoria Leong and co-I - A/Prof Domenico Campolo.

Key Responsibilities:

• Design and implement advanced audio and machine learning models for various applications, including Noise Suppression, Speaker Recognition, and Voice Activity Detection.
• Collaborate with our engineers to build large audio models and optimize audio generation.
• Develop unimodal and multimodal models for audio technology development and algorithm implementation.
• Analyze and process large-scale audio materials to maintain high-quality audio standards.
• Research and optimize audio generation models, converting the latest research findings into practical product features.
• Stay informed about the latest research developments in audio technology to ensure our solutions remain cutting-edge.

Job Requirements:

• Master's degree or higher in Audio Engineering, Computer Science, Signal Processing, Electronic Engineering, or related fields.
• 3+ years of work experience in Machine Learning or related areas, with a focus on audio signal processing theory.
• Proficiency in deep learning frameworks such as TensorFlow and PyTorch, with experience in building and optimizing complex audio generation models.
• Hands-on experience in speech enhancement, including Noise Suppression, Voice Activity Detection, Speaker Recognition, and Echo Cancellation.
• Familiarity with general-purpose programming languages such as Python, C/C++, or Java.
• Ability to read and understand English scientific literature and stay informed on the latest research developments in audio technology.
• Enthusiasm for applying Machine Learning or Artificial Intelligence Algorithms to Audio/DSP-related tasks.
• Experience of working in a fast-paced commercial/industry setting is preferred

Candidates with a proven track-record in one or more of these areas are welcome to apply. We will begin reviewing applications from July 2024 onwards, until the position is filled, and regret to inform that only shortlisted candidates will be notified.

Hiring Institution: NTU