When you join the growing BILH team, you're not just taking a job, youāre making a difference in peopleās lives.
We are seeking a highly motivated Staff Scientist with expertise in artificial intelligence (AI), machine learning, and magnetic resonance imaging (MRI) to support and advance cutting-edge translational research in cardiovascular imaging. The successful candidate will play a central role in the research, development, and validation of AI-enabled methods, with a primary focus on quantitative imaging and diagnostic and prognostic applications. Methodological efforts will leverage modern generative and vision-based models, such as generative adversarial networks (GANs), diffusion models, and transformer-based vision architectures, with an emphasis on robustness, reproducibility, and clinical relevance.
This position is well suited for a PhD-trained scientist who enjoys hands-on technical development, close collaboration with clinicians, engineers, and industry partners, and contributing to NIH-funded 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 computer science, electrical engineering, or biomedical engineering and have a minimum of five years of research-based experience (including PhD thesis) in artificial intelligence, computer vision, or medical imaging in an academic or research environment.
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 AI and MRI.
3. Summary of relevant coursework (unofficial transcripts are encouraged).
4. Annotated summaries (approximately 4ā6 sentences each) for the applicantās most significant scholarly works. These summaries should describe the key findings, scientific impact, and the applicantās specific role in each work. For middle-authorship contributions, applicants must clearly delineate their individual contributions.
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:
AI & Imaging Research
ā¢ Research and develop deep learning models for MRI reconstruction, segmentation, quantification, and image enhancement
ā¢ Design, optimize, and evaluate AI pipelines to improve image acquisition efficiency, image quality, and robustness
ā¢ Integrate AI methods with quantitative CMR imaging biomarkers, including myocardial blood flow, strain, and tissue characterization
ā¢ Develop and apply methods for multi-modality data integration, combining imaging, physiologic signals (e.g., ECG), genetic, and clinical data for diagnostic and prognostic modeling
ā¢ Perform rigorous model validation, including reproducibility testing, bias assessment, and external validation
ā¢ Design, develop, and implement user-friendly software platforms for clinical deployment of AI-enabled imaging tools
Scientific Leadership
ā¢ Serve as a technical lead on funded research projects (NIH R01s, industry collaborations)
ā¢ Contribute to study design, statistical analysis plans, and imaging endpoints
ā¢ Lead or co-author high-impact manuscripts, abstracts, and grant submissions
ā¢ Mentor trainees (PhD students, postdocs, research staff) Data & Infrastructure
ā¢ Build and maintain scalable AI/MRI pipelines (Python, PyTorch/TensorFlow, etc.)
ā¢ Work with large-scale imaging datasets and HPC/GPU environments (H200s GPUs)
ā¢ Collaborate on data harmonization, curation, and governance across multi-site studies Translational & Collaborative Work
ā¢ Partner closely with cardiologists, radiologists, MR physicists, and industry collaborators
ā¢ Support translation of AI tools toward clinical feasibility and regulatory readiness
ā¢ Present work at national and international scientific meetings
Preferred Qualifications
ā¢ PhD in Biomedical Engineering, Computer Science, Electrical Engineering, Medical Physics, or related field
ā¢ 5+ years of research experience in machine learning / deep learning / computer vision
ā¢ Demonstrated experience with medical imaging data
ā¢ Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow)
ā¢ Proven track record of publications in top-tier imaging journals (e.g., Radiology, Radiology: AI, Radiology: CTI, MRM, JCMR, MICCAI, IEEE TMI, IEEE TBME, CVPR, Medical Image Analysis).
Nice to Have Qualifications:
ā¢ Experience in cardiac MRI
ā¢ Familiarity with MRI physics, image reconstruction, or quantitative imaging
ā¢ Experience with generative models (diffusion models, super-resolution, image synthesis)
ā¢ Prior involvement in NIH-funded research
ā¢ Interest in clinical translation and real-world deployment
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 periods of time or move throughout the hospital campus.
Pay Range:
$60,320.00 USD - $150,009.60 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, geographyĀ of work location, job responsibilities, or other applicable factors permissible by law.Ā
As a health care organization, we have a responsibility to do everything in our power to care for and protect our patients, our colleagues and our communities. Beth Israel Lahey Health requires that all staff be vaccinated against influenza (flu) as a condition of employment.
More than 35,000 people working together. Nurses, doctors, technicians, therapists, researchers, teachers and more, making a difference in patients' lives. Your skill and compassion can make us even stronger.
Equal Opportunity Employer/Veterans/Disabled