Summary
The Department of Internal Medicine (Section of Cardiovascular Medicine) / Department of Radiology and Biomedical Imaging at the Yale School of Medicine is seeking an ambitious and talented Postdoctoral Associate in Cardiovascular Artificial Intelligence (AI) and Medical Imaging.
The successful candidate will join an interdisciplinary team bridging machine learning, clinical cardiology, and multi-modality biomedical imaging (e.g., Echocardiography, Cardiac MRI, Cardiac CT, and ECG data). The postdoc will focus on developing, evaluating, and translating state-of-the-art computer vision, multimodal deep learning models, and generative AI methods to improve the early detection, phenotyping, and risk stratification of cardiovascular diseases.
Designation
- Title: Postdoctoral Associate
- Classification: Full-time, Academic Postdoctoral Appointee
- Department/Division: Department of Internal Medicine (Cardiovascular Medicine) / Department of Radiology & Biomedical Imaging
- Institution: Yale University / Yale School of Medicine
Key Job Details
| Feature | Details |
| Position Title | Postdoctoral Associate – Cardiovascular AI & Medical Imaging |
| Hiring Organization | Yale University (Yale School of Medicine) |
| Location | New Haven, Connecticut, USA (In-person / On-campus) |
| Appointment Type | Full-Time (Initial 1-year appointment, renewable based on funding & performance) |
| Salary / Compensation | Commensurate with Yale Postdoctoral Compensation Policy and NIH NRSA guidelines |
| Benefits | Comprehensive Yale health, dental, vision, and retirement benefits package |
| Visa Sponsorship | J-1 / standard academic visa sponsorship available for international scholars |
| Application Deadline | Open until filled (Rolling reviews; priority review within 30 days) |
Research Area
- Primary Fields: Cardiovascular Data Science, Medical Image Analysis, Computer Vision, Deep Learning, Biomedical Informatics.
- Focus Areas:
- Multimodal deep learning integrating cardiac imaging (Echocardiography, MRI, CT) and structured/unstructured electronic health records (EHR).
- Foundation models and computer vision algorithms for automated segmentation, cardiac motion tracking, and disease phenotyping.
- Translation and deployment of trustworthy, fair, and interpretable clinical AI tools into real-world hospital workflows.
Location
- Primary Work Location: Yale School of Medicine, New Haven, CT 06520, USA.
Eligibility & Qualifications
Required Qualifications:
- Education: Ph.D. or M.D./Ph.D. (or equivalent terminal degree) in Biomedical Engineering, Computer Science, Data Science, Electrical Engineering, Medical Physics, Health Informatics, or a closely related quantitative field.
- Technical Skills:
- Proficiency in Python and modern deep learning frameworks (PyTorch, TensorFlow, MONAI, or TorchVision).
- Experience with medical imaging data formats (DICOM, NIfTI, etc.) and pre-processing pipelines.
- Strong foundation in statistical modeling, machine learning, and computer vision.
- Track Record: Demonstrated research productivity evidenced by first-author publications in peer-reviewed scientific journals (e.g., Nature Digital Medicine, Lancet Digital Health, JACC, Circulation) or leading AI conferences (e.g., MICCAI, CVPR, NeurIPS, IEEE TMI).
- Communication: Excellent written and oral English communication skills with the ability to work in multidisciplinary clinical and engineering teams.
Preferred Qualifications:
- Prior research experience specifically in cardiovascular imaging (Echo, CMR, Cardiac CT) or clinical electrocardiography (ECG).
- Experience with High-Performance Computing (HPC) environments and distributed GPU training.
- Experience deploying ML models in clinical IT systems or cloud platforms (AWS, GCP, Azure).
Job Description & Key Responsibilities
- Algorithm Development: Lead the development, training, and fine-tuning of machine learning and deep learning models for automated cardiovascular image analysis and disease prediction.
- Data Curation & Pipeline Engineering: Build robust data pipelines for extraction, harmonization, quality control, and pre-processing of large-scale clinical and imaging datasets.
- Publication & Dissemination: Author high-impact scientific manuscripts, contribute to grant proposals, and present research findings at major national and international conferences.
- Collaboration & Mentorship: Collaborate closely with cardiologists, radiologists, and software engineers, and mentor graduate students and postgraduate research associates within the lab.
- Compliance & Ethics: Adhere strictly to institutional review board (IRB) protocols, patient data privacy (HIPAA), and ethical AI principles.
How to Apply
Interested candidates should submit the following application materials in a single PDF file:
- Curriculum Vitae (CV): Comprehensive academic CV including a full publication list.
- Cover Letter: Highlighting your research experience, technical skills, career goals, and specific interest in cardiovascular AI.
- Research Statement: Brief summary of past research achievements and proposed postdoctoral research vision (1–2 pages).
- References: Contact information (names, affiliations, and emails) for 2–3 academic or professional referees.
Submission:
- Apply via the Yale Office for Postdoctoral Affairs Open Positions Portal or email application materials directly to the Principal Investigator / Faculty Contact listed on the posting.
Last Date for Apply
- Application Deadline: Open until filled.
- Applications are evaluated on a rolling basis; early application submission is strongly encouraged.
