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Postdoctoral Fellow Image Analyst NCI


Frederick, MD

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The Cancer Research Technology Program (CRTP) develops and implements emerging technology, cancer biology expertise and research capabilities to accomplish NCI research objectives. The CRTP is an outward-facing, multi-disciplinary hub purposed to enable the external cancer research community and provides dedicated support to NCI's intramural Center for Cancer Research (CCR). The dedicated units provide electron microscopy, protein characterization, protein expression, optical microscopy and genetics. These research efforts are an integral part of CCR at the Frederick National Laboratory for Cancer Research (FNLCR). CRTP scientists also work collaboratively with intramural NCI investigators to provide research technologies and expertise. At the Center for Molecular Microscopy (CMM), scientists collaborate with leading NCI researchers to develop and deploy new technologies for high-resolution 3-D electron microscopy (EM) of cells and tissues with research and/or clinical relevance.
The Postdoctoral Fellow, Image Analyst will:
Conduct R&D to create solutions to visualize and quantify features of interest from 3-D electron microscopy (EM) datasets
Apply deep learning algorithms to generate accurate models that can be used for classification, discovery, as well as hypothesis generation and testing in a variety of disease settings
Streamline existing image processing workflows using leading computing technologies
Extend existing segmentation solutions to large volume 3-D EM data
Research, develop and apply deep learning approaches to recognize features from high-resolution 3-D EM images of cells and tissue
Deploy new solutions across a range of systems: from local workstations to the NIH supercomputer
Innovate in a national laboratory environment focused on life sciences applications
To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below:
Possession of a PhD from an accredited college/university according to the Council for Higher Education Accreditation (CHEA) in a computing or image analysis related field. Foreign degrees must be evaluated for U.S. equivalency
No experience required beyond the Doctorate degree
Must be able to obtain and maintain a security clearance
Candidates with these desired skills will be given preferential consideration:
Demonstrated experience with image processing applications, with a record of peer-reviewed publications
Fluent in using Python
5 years of experience in image analysis/deep learning
Experience using high-performance computing environment
General experience in machine learning approaches
Familiarity with libraries for neural network applications (e.g. TensorFlow, PyTorch, Caffe, CNTK,...)
Familiarity with latest image processing techniques
Ability to work effectively in a Linux operating environment
Experience with application development using high-level languages
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