Postdoctoral Associate

2 days ago

Singapore Singapore-MIT Alliance for Research and Technology Full time

**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 academia, clinicians, industry, and policymakers, WITEC will ensure that its technological advancements are innovative, clinically validated, and suitable for industrial scale up.

**Key Responsibilities**:
1, Develop advanced AI solutions for analyzing time-series 2D/3D ultrasound data. Perform image segmentation, anomaly detection, and extraction of biomarkers for disease classification. Design deep learning models for multimodal image registration and alignment of ultrasound with ground-truth MRI data.

3, Develop AI-assisted robotic guidance tools for precise and automated ultrasound acquisition. Interface AI algorithms with robotic systems to adaptively control probe positioning and ultrasound imaging parameters.

4, Design and test intuitive human-machine interfaces to support non-specialist users in operating wearable ultrasound devices. Conduct quantitative and qualitative evaluations of AI models in simulated and real-world clinical scenarios. Integrate imaging, diagnostic reporting, and clinical data into a cohesive platform for intelligent diagnosis decision support. Enable clinicians to make informed decisions in cardiovascular care, improving patient outcomes, care quality, and cost-efficiency.

5. Perform other duties as assigned.

**Requirements**:
1. Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field, with expertise in computer vision or medical image analysis.

2. Demonstrated research experience in 2D/3D medical imaging using deep learning methods. Proved by strong track record of publications in top-tier AI and medical imaging conferences/journals.

3. Solid mathematical background, excellent programming skills, and proficiency in machine learning frameworks such as Python, C/C++, TensorFlow, and PyTorch.

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