Postdoctoral Research Fellow- Machine Vision/Image Analysis

Postdoctoral Research Fellowships (OCT Image Processing and Machine Learning)

Employer 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 (OCT) 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

Job Description

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, esophagus, colon

Guide research questions, design studies, and monitor the execution of those studies

Hold regular technical meetings.

Publish in world-leading high impact journals

Deliver milestones on time

Representative recent publications from our group include:

1.            Dong, J., C. Grant, B. Vuong, N. Nishioka, A.H. Gao, M. Beatty, G. Baldwin, A. Baillargeon, A. Bablouzian, P. Grahmann, N. Bhat, E. Ryan, A. Barrios, S. Giddings, T. Ford, E. Beaulieu-Ouellet, S.H. Hosseiny, I. Lerman, W. Trasischker, R. Reddy, K. Singh, M. Gora, D. Hyun, L. Queneherve, M. Wallace, H. Wolfsen, P. Sharma, K.K. Wang, C.L. Leggett, J. Poneros, J.A. Abrams, C. Lightdale, S. Leeds, M. Rosenberg, and G.J. Tearney, Feasibility and Safety of Tethered Capsule Endomicroscopy in Patients With Barrett's Esophagus in a Multi-Center Study. Clin Gastroenterol Hepatol, 2022. 20(4): p. 756-765 e3.
2.            Wartak, A., A.K. Kelada, P.A. Leon Alarcon, A.L. Bablouzian, O.O. Ahsen, A.L. Gregg, Y. Wei, K. Bollavaram, C.J. Sheil, E. Farewell, S. VanTol, R. Smith, P. Grahmann, A.R. Baillargeon, J.A. Gardecki, and G.J. Tearney, Dual-modality optical coherence tomography and fluorescence tethered capsule endomicroscopy. Biomed Opt Express, 2021. 12(7): p. 4308-4323.
3.            Osborn, E.A., G.J. Ughi, J.W. Verjans, Z. Piao, E. Gerbaud, M. Albaghdadi, H. Khraishah, M.B. Kassab, R.A.P. Takx, J. Cui, A. Mauskapf, C. Shen, R.W. Yeh, M.T. Klimas, A. Tawakol, G.J. Tearney*, and F.A. Jaffer*, Intravascular Molecular-Structural Assessment of Arterial Inflammation in Preclinical Atherosclerosis Progression. JACC Cardiovasc Imaging, 2021. 14(11): p. 2265-2267.
4.            Yin, B., Z. Piao, K. Nishimiya, C. Hyun, J.A. Gardecki, A. Mauskapf, F.A. Jaffer, and G.J. Tearney, 3D cellular-resolution imaging in arteries using few-mode interferometry. Light Sci Appl, 2019. 8: p. 104.
5.            Leung, H.M., S.E. Birket, C. Hyun, T.N. Ford, D. Cui, G.M. Solomon, R.J. Shei, A.T. Adewale, A.R. Lenzie, C.M. Fernandez-Petty, H. Zheng, J.H. Palermo, D.Y. Cho, B.A. Woodworth, L.M. Yonker, B.P. Hurley, S.M. Rowe, and G.J. Tearney, Intranasal micro-optical coherence tomography imaging for cystic fibrosis studies. Sci Transl Med, 2019. 11(504).

A Postdoctoral Research Fellowship in optical coherence tomography (OCT) machine learning classification is available in the Tearney Lab (www.tearneylab.org) at the Massachusetts General Hospital (MGH) in the Wellman Center for Photomedicine. This appointment will be made at the rank of postdoctoral fellow at Harvard Medical School. MGH's role as a leading teaching affiliate of Harvard Medical School and close ties to Harvard University and MIT provide an outstanding environment for developing and translating new medical imaging technologies with applications in basic and clinical research.

Job Requirements

A Ph.D. (or equivalent) in Computer Science or Engineering, Biomedical Engineering, Electrical Engineering, Physics, or a related field is required.

Required Skills

A background in using machine learning to solve problems in optical coherence tomography along with multiple publications

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.

Desired Skills

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, and familiarity working with data from several.

A working understanding of histological processing methods and identification of normal and abnormal tissue in several disease types

A working understanding of tissue optical properties

Contact Information

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 tearneylabsearch@partners.org

MGH is an equal opportunity employer.