Visiting Scientist

Beth Israel Lahey Health

7d•$155,002 - $184,995•Onsite

About The Position

We are seeking a highly motivated 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 development, validation, and deployment of AI-enabled methods, with emphasis on cardiac MRI (CMR), quantitative imaging, and diagnostic and prognostic applications. This position is ideal for a PhD scientist who enjoys hands-on technical development, close collaboration with clinicians, engineers, and industry partners, and contributing to NIH-funded, multi-center research programs, including active collaborations with Siemens Healthineers, with clear pathways toward clinical translation and impact.

Requirements

PhD in Biomedical Engineering, Computer Science, Electrical Engineering, Medical Physics, or related field
Strong background in machine learning / deep learning / computer vision
Demonstrated experience with MRI or medical imaging data
Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow)
Track record of peer-reviewed publications in imaging or AI-related fields

Nice To Haves

Experience in cardiac MRI
Familiarity with MRI physics, image reconstruction, or quantitative perfusion/flow
Experience with generative models (diffusion models, super-resolution, image synthesis)
Prior involvement in NIH-funded research or multi-center studies
Interest in clinical translation and real-world deployment

Responsibilities

Develop and implement deep learning models for MRI reconstruction, segmentation, quantification, and image enhancement
Design, optimize, and evaluate AI pipelines to improve image acquisition efficiency, image quality, and robustness
Integrate AI methods with quantitative CMR imaging biomarkers, including myocardial blood flow, strain, and tissue characterization
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
Perform rigorous model validation, including reproducibility testing, bias assessment, and external validation
Design, develop, and implement user-friendly software platforms for clinical deployment of AI-enabled imaging tools
Serve as a technical lead on funded research projects (NIH R01s, industry collaborations)
Contribute to study design, statistical analysis plans, and imaging endpoints
Lead or co-author high-impact manuscripts, abstracts, and grant submissions
Mentor trainees (PhD students, postdocs, research staff)
Build and maintain scalable AI/MRI pipelines (Python, PyTorch/TensorFlow, etc.)
Work with large-scale imaging datasets and HPC/GPU environments (H200s GPUs)
Collaborate on data harmonization, curation, and governance across multi-site studies
Partner closely with cardiologists, radiologists, MR physicists, and industry collaborators
Support translation of AI tools toward clinical feasibility and regulatory readiness
Present work at national and international scientific meetings