Staff Scientist- MRI Physics

Beth Israel Lahey Health; Boston (MA); On-site; USD 110,000 - 160,000; Full time

Job summary

Beth Israel Lahey Health is seeking a Staff Scientist to design, implement, and validate advanced MRI pulse sequences for cardiovascular imaging. The role emphasizes quantitative MRI, acquisition optimization, and accuracy, with collaboration across clinicians, engineers, and industry partners.

The candidate will work with modern ML approaches, including GANs and transformers, to improve efficiency, motion compensation, and image quality while ensuring reproducibility of quantitative

Qualifications

• PhD required in Medical Physics, Biomedical Engineering, or related field.
• 2–3 years postdoc experience in MRI sequence development or reconstruction.
• Experience translating MRI methods to clinical imaging applications.
• Publications in top imaging journals preferred.

Responsibilities

• Research and develop novel MRI pulse sequences for cardiovascular MRI.
• Apply deep learning to MRI reconstruction and quantification.
• Conduct imaging experiments on 3T Siemens MRI to evaluate performance of new sequences.

Skills

MRI pulse sequences

Deep learning

Quantitative MRI

Image reconstruction

Machine learning

Cross-functional collaboration

Education

PhD in Medical Physics

2–3 years postdoc experience

Tools

Siemens MRI

GPU clusters

NVIDIA hardware

Job description

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 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. Applicants must hold a PhD with additional 2-3 years of postdoc training 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. 3+ years of postdoctoral experience preferred.

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 inMRI, 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

Essential Responsibilities

• Conducts research in area of specialty.
• Has the authority to direct and support managers with functional area responsibilities.
• Has the direct responsibility to undertake the following employment actions: hiring, termination, corrective action and performance reviews.
• Has full responsibility for planning, monitoring and managing department budget.
• Direct Reports: None Indirect Reports: None

Required Qualifications

• Ph.D. and/or Medical Degree required.
• 0-1 years related work experience required, including, 1 year of supervisory/management experience required.
• Advanced technical computer skills as required for technical support specific to functional area and related systems.

Competencies

Written Communications: Ability to communicate complex information in English effectively in writing to all levels of staff, management and external customers across functional areas.

Oral Communications: Ability to verbally communicate complex concepts in English and address sensitive situations, resolve conflicts, negotiate, motivate and persuade others.

Knowledge: Ability to demonstrate broad and comprehensive knowledge of theories, concepts, practices and policies with the ability to use them in complex and/or unprecedented situations across multiple functional areas.

Teamwork: Ability to lead and direct multiple collaborative teams for large projects or groups both internal and external to the Medical Center and across functional areas. Results have significant implications for the management and operations of the organization.

Customer Service: Ability to lead operational initiatives to meet or exceed customer service standards and expectations in assigned unit(s) and/or across multiple areas 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