Data Scientist – Optical Coherence Tomography Processing
- Wellman Center for Photomedicine
- Location: Boston, MA
- Job Number: 7108350
- Posting Date: Aug 18, 2022
Job DescriptionEmployer Description
Guillermo (Gary) J. Tearney, M.D., Ph.D.
Tearney Lab – Wellman Center for Photomedicine
Massachusetts General Hospital
The Tearney Lab is an 80+ person multidisciplinary lab led by Guillermo (Gary) Tearney, MD, PhD. The goal of the Tearney Lab is to see every cell in the human body so that disease can be detected at its earliest stages when it can be cured.
To this end, the lab has pioneered multiple optical coherence tomography (OCT) devices that enable 3D imaging at the microscopic scale in living human patients. These technologies include multimodality OCT where OCT is combined with spectroscopy, fluorescence, and other optical techniques, ultrahigh-resolution OCT (µOCT) where the resolution is sufficiently detailed to visualize individual cells, and functional OCT that measures the function and metabolism of cells in living systems. These technologies are implemented in a variety of devices (endoscopes, catheters, capsules, implantable) that provide accessible imaging anywhere inside the body. The lab has major programs to overcome clinical diagnostic challenges in celiac disease, food allergy disorders, malnutrition, coronary artery disease, hearing loss, GI cancer, and cystic fibrosis, among others. Novel technologies are created using device development processes and tested and validated in over 15 ongoing single- and multi-center clinical studies.
To enable this broad translational research, the Tearney Lab is outfitted with:
• Robust engineering, quality, and clinical regulatory teams
• State of the art optical laboratories
• Two class 10,000 clean rooms
• Multiple rapid prototyping facilities
• Nanoscribe optical printing
• Machine learning core
The role will
- Focus on advancing state-of-the-art in automated cancer detection via medical image analysis to solve challenging problems in processing, evaluating, and interpreting clinical and pre-clinical data
- Develop a set of semi-automated and automated image processing and analysis applications, including segmentation, classification, registration, feature extraction and pattern detection
- The specific aim of the fellowship can be tailored to meet individual goals, which will provide an opportunity to build clinical, research, and publication experience
- Working closely with the technology development teams and clinical collaborators
- Implement analysis technologies in one or more of the following organ systems: heart, lungs, brain, ears, and the gastrointestinal tract
- Guide research questions, design studies, and monitor the execution of those studies
- Hold regular technical meetings.
- Deliver milestones on time
A masters or Ph.D. (desired) in Computer Science or Engineering, Biomedical Engineering, Electrical Engineering, Physics, or a related field is required.
A strong background in machine learning
Experience on deep learning frameworks such as PyTorch, Keras or TensorFlow
Experience with OCT image analysis and OCT machine learning
A strong understanding of classical image processing techniques using MATLAB, ImageJ, and Python. Techniques include spatial frequency domain filtering, lumen segmentation, and denoising data.
Intel Integrated Performance Primitives (IPP), embedded operating systems, Arduino, and GPU programming are helpful
An understanding of types of different types of in-vivo medical imaging systems such as fluorescence microscopy, spectroscopy, ultrasound, photoacoustics
An understanding of histological processing methods and identification of normal and abnormal tissue in several disease types
An understanding of tissue optical properties
Interested candidates are encouraged to send a CV accompanied by a cover letter describing any previous research training, specific areas of interest, and contact information for three letters of reference. Address correspondence to Dr. Gary Tearney, note the position you are applying for in the subject line, and send by email to [email protected]
MGH is an equal opportunity employer.