Postdoc Fellowship - Machine Learning in Digital Pathology

Thursday 8th September 2022

Organization National Cancer Institute, NIH
Location Bethesda, MD
Title Postdoc Fellowship - Machine Learning in Digital Pathology
Email Address

Seeking highly motivated research fellows for 3-year position working on development of deep learning-based approaches for histomorphological characterization of metastatic prostate cancer and its association with molecular profiling. Algorithm development and deployment will feature a diverse cohort of patient samples from an ongoing multi-institutional collaboration.

The Artificial Intelligence Resource, Molecular Imaging Branch within the Center for Cancer Research (CCR) at the National Cancer Institute (NCI) includes researchers with focus in translational applications of AI and computer vision in medical image analysis, including both radiology, digital pathology, and other medical imaging fields. This dynamic group works with clinical researchers to identify AI projects and solutions for oncology tasks related to disease diagnosis, monitoring, and prognosis. All fellows will be expected to interface with senior staff, clinical investigators, and other research fellows during design, development, and testing of algorithms. Fellows should anticipate being involved in all components of database development pertaining to each application, including dataset curation, annotation, and evaluation.

Candidates should hold a PhD degree in computer science, biostatistics/informatics, biomedical or electrical engineering, physics, mathematics or related fields.
Desirable skills: should be able to demonstrate programming knowledge/skills in one or more languages including Python, R, Matlab, C/C++, etc
Publication record of prior experience or expertise in quantitative image analysis or deep learning and/or machine learning is required, ideally in computer vision but not required
A successful candidate will be able to demonstrate ability to design and execute independent research projects including peer-reviewed publications, preparing and presenting preliminary data at research conferences, and strong communication skills to broad audience
1 year appointments renewable up to 3 years

To Apply:
Interested individuals should contact for further details and instructions to apply for this position