Associate Scientist, Digital Pathology (NCI) - Gaithersburg, MD | Biospace
Get Our FREE Industry eNewsletter

Associate Scientist, Digital Pathology (NCI)

Leidos Biomedical Research, Inc.

Gaithersburg, MD
Posted Date:
Position Type:
Full time
Job Code:
Required Education:
Bachelors Degree
Areas of Expertise Desired:
Cancer, Genomics, Imaging, Molecular, Pathology,

Job Description

Leidos Biomedical Research, Inc. (LBRI), a wholly owned subsidiary of Leidos, operates the Frederick National Laboratory for Cancer Research (FNLCR). FNLCR is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI). It is the only FFRDC dedicated to biomedical research. Through its status as an FFRDC, FNLCR provides NCI and others with a unique national resource to accelerate the development and delivery of effective preventive, diagnostic, and therapeutic products for cancer and AIDS.

The breadth of FNLCR’s activities spans the research and development spectrum, including investigator-initiated, hypothesis-driven research into cancer and AIDS; advanced technology programs focused on genetics and genomics, proteins and proteomics, imaging, nanotechnology, bioinformatics, and laboratory animal sciences; clinical operations in support of NCI and National Institute of Allergy and Infectious Diseases (NIAID)-sponsored clinical trials, as well as NCI drug discovery and development efforts; and management and operations of biopharmaceutical development and manufacturing programs under current Good Manufacturing Practice conditions for NCI and NIAID. Administrative, procurement, financial, safety, and facilities support is provided to these R&D activities through state-of-the-art business processes.  LBRI has approximately 1,900 employees and manages an annual operating budget of approximately $450M.

For more information about Leidos Biomedical Research Inc., please visit our webpage at

The Cancer Genomics Research Laboratory (CGR) investigates the contribution of germline and somatic genetic variation to cancer susceptibility and outcomes in support of the NCI's Division of Cancer Epidemiology and Genetics (DCEG). Working in concert with epidemiologists, biostatisticians and basic research scientists in DCEG’s intramural research program, CGR provides the capacity to conduct genome-wide discovery studies and targeted regional approaches to identify the heritable determinants of various forms of cancer.

The Cancer Genomics Research (CGR) laboratory in Gaithersburg, MD, is a fast-paced, high-throughput organization dedicated to the support of molecular, genetic and epidemiologic studies for investigators at the National Cancer Institute's Division of Cancer Epidemiology & Genetics (DCEG).  The Division includes over 70 principal investigators in epidemiology, genetics, and biostatistics who conduct multidisciplinary family- and population-based research to discover the genetic and environmental determinants of cancer, and new approaches to cancer prevention. This includes the design and analysis of high throughput studies using various types of “–omics” technologies such as array- and sequence-based genome-wide association studies, studies of tumor characteristics using integrated genomic data analysis and molecular epidemiologic studies based on novel metabolomic and microbiomic assays. DCEG maintains a rich resource of tissue specimens from a diverse array of cancer types to enable these studies.  Included in its over 12 million biospecimen collection, DCEG currently stores over 300,000 tissue specimens from 275 family- and population-based studies, with FFPE tissues stored as blocks, cores, tissue microarrays (TMAs), and slides.

The Associate Scientist will be responsible for establishing and executing digital pathology activities to support molecular pathology epidemiological studies, in coordination with existing CGR staff, management and IT resources. General responsibilities include: 1) digitization of standard and TMA slides, including maintenance and operation of high throughput automated scanning instrumentation, monitoring quality of digitized images, and training CGR and DCEG collaborators on use of viewing software, 2) quantitative and qualitative image analysis, including training of algorithms provided by software manufacturers to most accurately identify sub-cellular staining patterns and tissue recognition features for external and internal projects, 3) development of new algorithms and new analysis methodologies in consultation with technology providers, DCEG pathologists and investigators, 4) identify gaps in analytical methodologies, and work with technology providers, DCEG, CGR and external collaborators to evaluate, beta test and enable new technologies in the facility, 5) develop and implement quality assurance procedures for digitization & analysis. This will include routine testing and remediation activities, SOP documentation and close coordination with existing CGR QA/QC infrastructure, 6) independently create training documentation and provide training to DCEG researchers and external collaborators on the use of the instrumentation and its associated software, 7)routine presentations to internal and external collaborators with updates on developments in the facility on image digitization and analysis, and 8) contribute to the writing of scientific manuscripts with DCEG scientists, where image analysis has been performed


Possession of a Bachelor's degree from an accredited college/university according to the Council for Higher Education Accreditation (CHEA) in a field related to biomedical research or four (4) years related experience in lieu of degree. Foreign degrees must be evaluated for U.S. equivalency
A minimum of ten (10) years of progressively responsible and relevant scientific experience.
Detailed experience with digital pathology imaging and data management systems (i.e. PathXL Xplore, Aperio eSlide Manager, etc.)
Demonstrated in-depth knowledge of imaging software algorithms (for nuclear, cell surface, cytoplasmic and microvessel density) as well as understanding of the scientific validity of the analysis, statistical analysis and recognition of tissue features.
Demonstrated ability to work independently on multiple complex technical projects or in the development of advanced techniques and procedures from which publications have resulted.
Team oriented with excellent written and verbal communication skills, with demonstrated ability to train others as well as self-educate in current digital imaging and analytical techniques
Masters or Ph.D. in pathology or a related discipline such as biology, chemistry or molecular biology
Experience in histological processes and morphological stains, including immunohistochemistry, in situ hybridization and immunofluorescence
Experience in bright-field microscopy
Experience in the field of molecular pathology with a strong publication record