We are seeking a highly motivated Staff Scientist with strong interest and expertise in the development and application of advanced MRI techniques to join the Cardiovascular MR Research Center under the mentorship of Prof. Reza Nezafat. The successful candidate will play a central role in the design, implementation, and validation of MRI pulse sequences and image acquisition strategies for cardiovascular imaging, with a particular emphasis on quantitative MRI methods. The work will involve developing and optimizing acquisition and reconstruction approaches for techniques such as quantitative perfusion, mapping, and motion-robust imaging, with close attention to MRI physics, sequence efficiency, and quantitative accuracy. Methodological efforts will integrate modern machine learning approaches—including generative and vision-based models such as generative adversarial networks, diffusion models, and transformer-based architectures—to enhance image acquisition efficiency, motion compensation, signal-to-noise ratio, and contrast fidelity, while preserving the accuracy and reproducibility of quantitative measurements across cardiovascular MRI sequences. This position is well suited for a PhD-trained scientist with 2-3 years of postdoc training who enjoys MRI technical development, close collaboration with clinicians, MRI physicists, engineers, and industry partners, and contributing to NIH-funded translational research programs. The role includes active collaborations with Siemens Healthineers and offers clear pathways toward clinical translation and real-world impact. The successful candidate will have access to a well-established research infrastructure, including a state-of-the-art 3T Siemens MRI system for advanced cardiovascular imaging and a dedicated high-performance computing environment with NVIDIA H200 GPU clusters to support large-scale deep learning model development, training, and evaluation.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree