AI Research Scientist – Medical Imaging Analysis Full-time

AI Research Scientist

We are seeking a talented AI Research Scientist to join Data Science team of Biometrics and Data Science in China R&D. He/she will be working on cutting-edge medical imaging analysis projects. This role offers the opportunity to develop and refine AI models for clinical applications, working with multimodal medical imaging data including CT, MRI, and digital pathology. You will collaborate with a cross-functional team and contribute to innovative AI solutions that address real-world healthcare challenges.

On-site: Beijing or Shanghai, China

Key Responsibilities

• Develop and refine deep learning models for medical imaging analysis, including CT, MRI, and whole-slide pathology images
• Implement and optimize state-of-the-art computer vision architectures (e.g., 3D Swin Transformers, attention-based mechanisms) for medical image understanding
• Work with multimodal data integration, combining imaging with clinical and molecular data
• Preprocess and quality-control large-scale medical imaging datasets, ensuring data standardization and artifact detection
• Implement multiple instance learning (MIL) approaches for weakly-supervised histopathology analysis
• Conduct model validation and performance evaluation using rigorous statistical methods
• Collaborate with clinical partners (oncologists, pathologists, radiologists) to understand domain requirements and validate model outputs
• Work cross-functionally with global team members across different time zones and locations
• Contribute to technical documentation, research papers, and presentations
• Stay current with latest advances in medical imaging AI and foundation models

Required Qualifications

• PhD in Computer Science, Biomedical Engineering, Electrical Engineering, or related field (or Master's degree with exceptional relevant experience)
• Strong expertise in deep learning frameworks, particularly PyTorch
• Proven experience with medical imaging analysis (CT, MRI, pathology, or related modalities)
• Solid understanding of computer vision architectures: CNNs, Vision Transformers, attention mechanisms
• Experience with 3D medical image processing and analysis
• Proficiency in Python and scientific computing libraries (NumPy, SciPy, scikit-learn)
• Knowledge of medical imaging preprocessing: normalization, registration, segmentation
• Strong analytical and problem-solving skills
• Excellent communication skills in English; ability to collaborate with international teams
• Ability to work independently and as part of a collaborative team

Preferred Qualifications

• Experience with foundation models for medical imaging (e.g., UNI for pathology, medical vision-language models)
• Hands-on experience with attention-based multiple instance learning (MIL) for whole-slide image analysis
• Knowledge of 3D Swin Transformers or similar hierarchical vision architectures
• Experience with multimodal data fusion and cross-modal learning
• Familiarity with self-supervised learning and contrastive learning methods
• Publications in top-tier venues (CVPR, ICCV, ECCV, MICCAI, Medical Image Analysis, IEEE TMI, Nature/Science journals)
• Experience with clinical trial data or regulatory compliance (HIPAA, GDPR)
• Understanding of oncology or other clinical domains
• Experience with distributed training and GPU optimization
• Contributions to open-source medical imaging projects

What We Offer

• Opportunity to work on impactful medical AI projects with real clinical applications
• Collaboration with leading clinical institutions and research partners globally
• Access to state-of-the-art computing resources and large-scale medical imaging datasets
• Cross-functional teamwork with domain experts in oncology, pathology, and radiology
• Professional development opportunities including conferences and publications
• Dynamic, innovative work environment with cutting-edge AI research