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.
Key Responsibilities:
• Research and develop novel MRI pulse sequences for various cardiovascular MRI applications
• Develop and apply deep learning methods to support MRI reconstruction, quantification, and image enhancement in conjunction with novel pulse sequence development.
• Perform imaging experiments using the 3T Siemens system to evaluate the performance of novel pulse sequences, image reconstruction and image enhancement
Preferred Qualifications:
• PhD in Medical Physics, Biomedical Engineering, Computer Science, Electrical Engineering, or related field
• 3+ years of research experience in MRI, focused on technical development
• Experience in pulse sequence programming on major MRI vendor platforms (e.g., Siemens, GE, Philips or United Imaging)
• Proven track record of publications in top-tier imaging journals (e.g., Radiology, Radiology: AI, Radiology: CTI, MRM, JMRI, JCMR).
Job Description:
Primary Responsibilities:
– Abides by the institutional policies of BIDMC relating to health and safety, equality of opportunity and data storage and management. (essential)
– As a member of the research team, actively pursues research under the supervision of a principal investigator while developing skills for independent work. (essential)
– Receives training in and performs duties contributing to the investigational work of the team including formulation of research questions and design, conduct of experiments, and evaluation of results. (essential)
– Prepares and publishes scientific manuscripts under direction of PI. (essential)
– Develops expertise in desired lab skills/informatics/ physics/clinical research. Develops proficiency with research tools and equipment. Develops ability to work with more independence as the fellowship progresses (essential)
– Develops new ideas that promote current research; brings new expertise to the research program. (essential)
– teaching skills and provide supervision of students and their projects when appropriate. (essential)
– Engages in collaborative meetings with other research groups. Attends and leads scientific seminars. (essential)
– Learns to identify, acknowledge and correct deficiencies in one's own performance. (essential)
– Under the direction of PI, pursues/secures independent funding near the end of the fellowship. (essential)
Required Qualifications:
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Doctoral Degree or M.D.
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0-1 year of postdoctoral research experience in academic or industrial lab setting, and/or teaching assistantship in a university setting, and/or residency, and/or clinical duties beyond that of the qualifying doctoral degree.
Competencies:
Decision Making: Ability to make decisions that are guided by general instructions and practices requiring some interpretation. May make recommendations for solving problems of moderate complexity and importance.
Problem Solving: Ability to address problems that are varied, requiring analysis or interpretation of the situation using direct observation, knowledge and skills based on general precedents.
Independence of Action: Ability to follow precedents and procedures. May set priorities and organize work within general guidelines. Seeks assistance when confronted with difficult and/or unpredictable situations. Work progress is monitored by supervisor/manager.
Written Communications: Ability to summarize and communicate in English moderately complex information in varied written formats to internal and external customers.
Oral Communications: Ability to comprehend and communicate complex verbal information in English to medical center staff, patients, families and external customers.
Knowledge: Ability to demonstrate in-depth knowledge of concepts, practices and policies with the ability to use them in complex varied situations.
Team Work: Ability to lead collaborative teams for larger projects or groups both internal and external to the Medical Center and across functional areas. Results have implications for the management and operations of multiple areas of the organization.
Customer Service: Ability to provide a high level of customer service and staff training to meet customer service standards and expectations for the assigned unit(s). Resolves service issues in the assigned unit(s) in a timely and respectful manner.
Physical Nature of the Job:
Light work: Exerting up to 20 pounds of force frequently to move objects. Some elements of the job are sedentary, but the employee will be required to stand for periods of time or move throughout the hospital campus.
Pay Range:
$60,320.00 USD – $90,001.60 USD
The pay range listed for this position is the annual base salary range the organization reasonably and in good faith expects to pay for this position at this time. Actual compensation is determined based on several factors, that may include seniority, education, training, relevant experience, relevant certifications, geography of work location, job responsibilities, or other applicable factors permissible by law.
