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Ultrasound Post-Doctoral Scholar​/Research Scientist

Job in Northern, Floyd County, Kentucky, USA
Listing for: Mass General Brigham Incorporated
Full Time position
Listed on 2026-10-17
Job specializations:
  • Science
    Research Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 96000 USD Yearly USD 60000.00 96000.00 YEAR
Job Description & How to Apply Below
## Ultrasound Post-Doctoral Scholar / Research Scientist Apply:
Onsite:
Boston-MA:
Full time:
Posted Today:
RQ4082879

Site:
The General Hospital Corporation Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
** Job Summary
** APPLY BY EMAIL ONLY - APPLICATION INSTRUCTIONS BELOW    We seek a talented and motivated ultrasound scientist/engineer to join our collegial and diverse multidisciplinary team.

The right candidate will have a strong background in ultrasound beamforming, shear wave elastography and an excellent understanding of ultrasound scattering physics and signal processing. Our goal is to transform medical ultrasound diagnosis through work that spans hardware and algorithm development focused on image reconstruction and analysis with an integrated clinical translational component. This is a unique opportunity to be part of a highly energetic multidisciplinary group working to translate research into clinical care.

The lab comprises more than 15 people distributed across clinical, translational, machine learning, and acoustic signal processing programs. This role is in the acoustic signal processing program, with three faculty offering excellent supervision to 2 to 4 post-doctoral research fellows.
The successful candidate will be appointed at the Massachusetts General Hospital and Harvard Medical School and will be expected to proactively develop research interests and to work effectively with others. Candidates seeking creative academic careers will have excellent growth opportunities, access to committed mentors, assistance with defining an early career trajectory, and mentored opportunities to apply for grants. There will be opportunities for mentorship from collaborating MIT and Harvard scientists.

Across a wide range of projects, our laboratory has developed expertise in advanced signal processing and machine learning with opportunities to gain exposure to these techniques.
The successful applicant will:  
• Work collaboratively with a highly motivated and collegial team of physicians, clinical researchers, computer scientists, and engineers to solve important medical problems in a world-class research facility.  
• Have access to a vast amount of high-quality medical imaging and pathologic data, advanced computing facilities, a friendly environment, and an unparalleled community of basic and clinical scientists.  
• Gain a deep understanding of key problems in medical imaging.  
• Gain knowledge and understanding of important disease processes.
** Qualifications
* *** Requirements:
*** PhD in Electrical Engineering, Biomedical Engineering, Medical Physics, Acoustics, Applied Physics, Applied Mathematics, Computational Statistics, Computer Science, or a related discipline.
* Strong knowledge of ultrasound wave propagation and scattering physics, signal processing, and experience with medical ultrasound instrumentation is required.
* Excellent understanding of beam formation processes emphasizing phase aberration correction, local speed of sound estimation, novel transmit-receive patterns, and estimation of coherent aperture size.
* Strong communication skills in written and verbal English are required.
* Proficiency in one or more programming languages, especially C++, MATLAB, Python, or R, is required.
* Experience with machine learning and shear wave…
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