Postdoctoral Associate
3 days ago
**Project Overview**:
**The Wearable Imaging for Transforming Elderly Care (WITEC)** interdisciplinary research group (IRG) is committed to creating next-generation wearable imaging technologies tailored for aging populations. By combining expertise in wearable transducers, biomedical imaging, materials science, data analytics, and healthcare innovation, WITEC aims to design solutions that will improve quality of life, support preventative medicine, and reduce healthcare burdens. Specific objectives include the development of wearable ultrasound imaging systems for doing cardiovascular echography, AI-powered diagnostic algorithms, and integration with digital health platforms for real-time monitoring and clinical decision support.
WITEC brings together interdisciplinary researchers from MIT and Singaporean institutions, including hospitals and research agencies. Through deep collaboration with local partners, including clinicians, industry, and policymakers, WITEC will ensure that its technological advancements are innovative, clinically validated, and suitable for industrial scale up.
**Responsibilities**:
1. Lead the development of wearable ultrasound systems for long-term cardiovascular monitoring. Investigate 3D ultrasound imaging modalities for continuous assessment of cardiac function in aging populations.
2. Process raw RF data from wearable ultrasound arrays using advanced beamforming techniques. Develop image reconstruction pipelines and extract clinically relevant metrics such as cardiac volume and ejection fraction.
3. Design and implement AI algorithms for tasks such as image quality assessment, view recognition and classification, image segmentation and registration, and automated cardiac condition detection and diagnosis.
4. Work closely with clinical partners to support protocol development, data acquisition, and analysis for pilot studies and clinical validation.
5. Perform other duties as assigned.
**Requirements**:
1. Ph.D. in Biomedical Engineering, Computer Science, Electrical Engineering, or a related discipline.
2. Solid background in medical ultrasound imaging, signal processing, or machine learning.
3. Proficiency in programming languages and environments such as Python, MATLAB, or C++.
4. Hands-on experience with ultrasound systems, particularly Verasonics or similar platforms is preferred.
5. Experience in echocardiography or cardiovascular image analysis is highly desirable. Experience with advanced ultrasound techniques such as Doppler imaging, harmonic imaging, or quantitative ultrasound is preferred.
6. Prior experience in AI-assisted ultrasound scan guidance or computer-aided diagnosis is preferred.
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