Senior Research Scientist

4 days ago


Singapur, Singapore MedClarity Full time

Senior Research Scientist - Computer Vision & Deep Learning Theia Health is at the forefront of transforming cardiac care through cutting‑edge AI solutions. Our mission is to revolutionize cardiac analysis by leveraging advanced computer vision to process CT DICOM volumes. We enable faster, more accurate assessments of critical cardiac markers such as coronary calcium, epicardial adipose tissue (EAT), and stenotic plaque. Join us to innovate in a high‑impact field that directly improves patient outcomes. This position is open only to candidates based in Singapore. Key Responsibilities Develop and enhance state‑of‑the‑art computer vision models for 2D/3D analysis of cardiac CT volumes. Lead fundamental research into attention mechanisms and multi‑scale architectures tailored for volumetric medical data. Drive innovation in adapting and scaling vision transformers and modern ConvNet architectures for medical imaging, including DICOM processing. Design novel approaches for accurate and efficient 3D analysis of anatomical structures. Build and optimize scalable processing pipelines for large volumetric datasets. Publish high‑impact research at top‑tier ML and computer vision conferences. Mentor researchers and contribute to key architectural decisions across projects. Qualifications Bachelor/Master’s/Ph.D. in Computer Science, Machine Learning, Computer Vision, or a related field. Strong publication record at top conferences (e.g., NeurIPS, ICML, ICLR). Expertise in vision transformer architectures and advanced innovations. Expertise in 3D vision architectures and volumetric data processing. Expertise in attention mechanisms and self‑supervised learning methodologies. Hands‑on experience with large‑scale data processing pipelines. Proficiency in PyTorch/TensorFlow and distributed training systems. Preferred Qualifications Experience working with 3D medical imaging data, including DICOM workflows. Proven track record of architectural innovation in computer vision. Expertise in efficient inference and model optimization for deployment. Familiarity with medical imaging workflows, particularly in cardiac imaging. #J-18808-Ljbffr



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