About this role
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 elastography is desirable.
- Experience with Linux and image analysis skills is desirable.
- Software beamformation experience and experience with the Verasonics platform is desirable.
- A demonstrated record of high-quality publication in ultrasound-related journals will be advantageous.
- Qualified candidates should be self-motivated and able to work independently and collaboratively.
The salary range for this position is $60,000 to $96,000 annually.
Additional Job Details (if applicable)
IMPORTANT – APPLICATION INSTRUCTIONS
Please do not apply through the Workday “Apply” button.
This position is being posted for informational purposes only. To be considered, please submit the following directly to the hiring managers by clicking the links below:
- Cover letter describing research experience, interests and goals
- CV with a full list of publications and a link to a GitHub profile (if available)
- Three references (including one from a current supervisor) to
Please note: Applications submitted through Workday will not be forwarded to the hiring manager and may not be reviewed .
Remote Type
Onsite
Work Location
55 Fruit Street
EEO Statement:
1200 The General Hospital Corporation is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran’s Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.