Postdoctoral Researcher in Federated Learning for Healthcare Imaging
2 weeks ago
We are seeking a highly motivated Postdoctoral Researcher to contribute to a groundbreaking research program focused on federated learning for healthcare imaging collaboration.
This exciting opportunity is part of a prestigious Turing AI World-Leading Researcher Fellowship and a grant that has assembled a substantial multi-site fetal echocardiography dataset encompassing both normal and congenital heart disease cases.
As a member of the esteemed Noble research group at the Institute of Biomedical Engineering, you will play a pivotal role in designing and evaluating innovative federated learning algorithms for video and multi-modal imaging data acquired across diverse clinical sites.
Key Responsibilities:
- Develop and implement cutting-edge federated learning algorithms tailored for healthcare imaging applications.
- Conduct rigorous testing and evaluation of proposed algorithms on existing clinical datasets and potentially collaborate with international partners to expand the research scope.
- Contribute to the publication of research findings in leading computer vision, machine learning, and medical image conferences and journals.
Qualifications:
- A PhD/DPhil (or near completion) in Federated Learning for Healthcare Imaging or a closely related field.
- A strong publication record demonstrating expertise in federated learning, computer vision, and/or medical image analysis at top-tier international conferences and journals.
- In-depth theoretical and practical knowledge of relevant methodologies and techniques in federated learning.
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