Full-Time

Postdoctoral Associate

Posted on 2/21/2026

University of Miami

University of Miami

No salary listed

Company Does Not Provide H1B Sponsorship

Miami, FL, USA

In Person

Category
Lab & Research (1)
Required Skills
Neural Networks
Machine Learning
3D Modeling
FEM/FEA
Requirements
  • Ph.D. in Computer Science, Biomedical Engineering, or related field with a strong background in artificial intelligence, machine learning, or deep learning.
Responsibilities
  • Develop and apply AI and machine learning methods to derive generalized and predictive models from CFD and FEA results to enhance understanding of stenting techniques and their impact on coronary vessels.
  • Create 3D anatomical models of coronary vessels and cardiovascular structures from imaging data using advanced AI techniques, incorporating patient-specific details for simulation-ready models used to simulate medical procedures and evaluate device performance.
  • Contribute to the design and execution of in silico clinical trials leveraging AI-generated 3D models and simulations to test cardiovascular devices, collaborating with regulatory bodies and industry partners to validate device performance and predict patient outcomes in virtual settings.
  • Generate more comprehensive stent finite element analysis morphometry results by applying AI techniques to existing FEA simulations to enable detailed predictions of stent performance and patient outcomes.
  • Collaborate with clinicians, engineers, and researchers to integrate AI-driven methods into current research frameworks, contributing to publications and conference presentations.
  • Handle large datasets including medical imaging data, ensure proper implementation of AI models, and maintain the integrity and security of patient information.
  • Prepare detailed reports, manuscripts for publication, and grant applications to support ongoing research and future funding.
Desired Qualifications
  • Strong programming skills in Python, MATLAB, or C++ and experience with machine learning frameworks such as TensorFlow or PyTorch.
  • Familiarity with medical imaging processing and reconstruction techniques.
  • Experience with coronary artery disease modeling and simulation.
  • Previous experience working in a clinical or medical research setting.

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