Image Analyst - Machine Learning

Job ID: req2689
Employee Type: exempt full-time
Division: Cancer Research Technology Program
Facility: Frederick: ATRF
Location: 8560 Progress Dr, Frederick, MD 21701 USA

The Frederick National Laboratory is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI) and operated by Leidos Biomedical Research, Inc. The lab addresses some of the most urgent and intractable problems in the biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, applications of nanotechnology in medicine, and rapid response to emerging threats of infectious diseases.

Accountability, Compassion, Collaboration, Dedication, Integrity and Versatility; it's the FNL way.

PROGRAM DESCRIPTION

At Frederick National Laboratory, the Cancer Research Technology Program (CRTP) is a multi-disciplinary hub where emerging technologies, biological expertise and research capabilities are developed and implemented in collaboration with intramural National Cancer Institute investigators and other researchers. Within the CRTP is the Center for Molecular Microscopy (CMM); in our group, scientists work in a highly collaborative environment to develop and deploy cutting-edge technologies for high-resolution 3-D volume electron microscopy (volume EM) and correlative microscopy (CLEM) of cells and tissues with research and/or clinical relevance. Our group works on innovations in sample preparation, imaging strategies, image processing, and data visualization, analysis and handling.

KEY ROLES/RESPONSIBILITIES

Working at a cutting-edge imaging lab in a national laboratory environment, the Image Analyst will create solutions to visualize and quantify features of interest from 2D and 3D electron microscopy (EM) datasets. S/he will apply machine learning and deep learning (ML/DL) algorithms for image classification and segmentation to aid discovery and hypothesis generation/testing in a variety of disease settings.

• Research and develop ML/DL approaches to recognize features from large-volume, high-resolution EM images of cells and tissues
• Adapt and apply existing image processing workflows to EM data to deliver visual and quantitative results to collaborators
• Handle large image data and track project metadata robustly
• Clear documentation and resilient workflows that can work on local workstations and NIH clusters

BASIC QUALIFICATIONS

To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below:

• Possession of Bachelor's degree from an accredited college/university according to the Council for Higher Education Accreditation (CHEA) in a related computing field or four (4) years relevant experience in lieu of degree. Foreign degrees must be evaluated for U.S. equivalency.
• Research Associate I - In addition to the education requirement, a minimum of two (2) years of related experience
• Research Associate II - In addition to the education requirement, a minimum of five (5) years of progressively responsible experience
• Fluent in using Python, and ease with libraries for neural network applications (e.g. TensorFlow, PyTorch)
• Experience in image analysis/machine or deep learning
• Ability to obtain and maintain a security clearance

PREFERRED QUALIFICATIONS

Candidates with these desired skills will be given preferential consideration:

• Master's degree in a computing or image analysis related field
• Demonstrated experience with image processing applications, with a record of open-source solutions on Github
• General experience in machine learning approaches and latest image processing techniques, especially for electron microscopy
• Experience with application development using high-level languages, ideally for commercial products
• Familiarity with high-performance computing environment

Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)

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