When you join the growing BILH team, you're not just taking a job, you’re making a difference in people’s lives. We are seeking a highly motivated Research Fellow with strong interest and expertise in the development and application of advanced cardiovascular 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 who enjoys hands-on 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. Applicants must hold a PhD in medical physics, electrical engineering, or biomedical engineering with research experience in MRI sequence development, image reconstruction, and/or quantitative MRI, with demonstrated experience integrating AI-based methods. Application Instructions: In addition to a curriculum vitae (CV), applicants are required to upload one combined PDF file containing the following materials, organized in the order listed below: 1. Cover letter describing research interests, relevant prior experience, career goals, and contact information for three references. 2. Brief research statement outlining technical expertise, research contributions, and areas of interest related to MRI. 3. Summary of relevant coursework (unofficial transcripts are encouraged). 4. Annotated summaries (approximately 4–6 sentences each) for the applicant’s most significant scholarly works. These summaries should describe the key findings, scientific impact, and the applicant’s specific role in each work. For middle-authorship contributions, applicants must clearly delineate their individual contributions. 5. 2-3 representative peer-reviewed publications All required application materials must be compiled into a single PDF file and uploaded at the time of application. Incomplete applications or applications that do not follow these submission instructions will not be considered.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
Number of Employees
1,001-5,000 employees