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The Department of Pathology and Cell Biology at Columbia University Medical center seeks a research pathologist to become a researcher on NIH-Funded research studies investigating functional biomarkers of breast cancer and their role in the prediction of breast cancer outcome and survival and how such biomarkers may be differentially predictive based on patient ethnicity, race, and genetic ancestry.  This translational research project will study proteomic, genomic, and epigenomic features and functional biomarkers of breast cancer outcomes using tissue for multiple ethnically diverse breast cancer cohorts from rural, urban, and metropolitan populations in the United States. The research program features an integrated morphological and computational profiling of multi-omic features of clinical breast cancer tissues using a variety of tissue-morphology-based approaches including immunohistochemistry, multiplex immunofluorescence, multiplex immunohistochemistry, and proximity-based ligation assays, that will be processed and analyzed by digital and computational pathology analytical pipelines to develop new and novel histological biomarkers of disease.  Emphasis on integrating patient sample gene expression, gene mutational signatures with spatial properties of the tumor and immune tumor micro-environment using multiplex platforms will be the major approach employing multiple state-of-the-art digital pathology platforms, and cutting edge digital pathology analytic software packages (including Halo, Visiopharm, Aperio, and QUPATH) to define a quantitative relationship between tissue features including protein, nucleic acid, tumor mutational profiles, and epigenomic tumor features.

At CUIMC, we stand together because diverse experiences, perspective, and values enrich every dimension of our work. Join our team and see how your unique skills and experiences can create a real impact by changing lives.

Job Function:

• Immunohistochemical staining and analysis of patient breast cancer tissues
• Morphological assessment of patient breast cancer tissues
• Complex analysis of tumor and tumor microenvironment to become a researcher on NIH-Funded research studies investigating functional biomarkers of breast cancer and their role in the prediction of breast cancer outcome and survival and how such biomarkers may be differentially predictive based on patient ethnicity, race, and genetic ancestry. 
• This translational research project will study proteomic, genomic, and epigenomic features and functional biomarkers of breast cancer outcomes using tissue for multiple ethnically diverse breast cancer cohorts from rural, urban, and metropolitan populations in the United States.
• Integrated morphological and computational profiling of multi-omic features of clinical breast cancer tissues using a variety of tissue-morphology-based approaches including immunohistochemistry, multiplex immunofluorescence, multiplex immunohistochemistry, and proximity-based ligation assays, that will be processed and analyzed by digital and computational pathology analytical pipelines to develop new and novel histological biomarkers of disease.
•  Emphasis on integrating patient sample gene expression, gene mutational signatures with spatial properties of the tumor and immune tumor micro-environment using multiplex platforms will be the major approach employing multiple state-of-the-art digital pathology platforms, and cutting edge digital pathology analytic software packages (including Halo, Visiopharm, Aperio, and QUPATH) to define a quantitative relationship between tissue features including protein, nucleic acid, tumor mutational profiles, and epigenomic tumor features.

Lab Mission/Purpose:

Emphasis on integrating patient sample gene expression, gene mutational signatures with spatial properties of the tumor and immune tumor micro-environment using multiplex platforms will be the major approach employing multiple state-of-the-art digital pathology platforms, and cutting edge digital pathology analytic software packages (including Halo, Visiopharm, Aperio, and QUPATH) to define a quantitative relationship between tissue features including protein, nucleic acid, tumor mutational profiles, and epigenomic tumor features.These features will be used to develop prognostic gene signatures and define biological pathways that will improve breast cancer diagnosis, increase accuracy in predicting response to therapy, and provide new insight into breast cancer subclassification, prevention, and intervention.  Mechanism and pathway identification will be validated in both in vitro and in vivo approaches using defined breast cancer cell lines and tissue based in vivo murine studies. Studies in both patients samples and experimental breast cancer cell lines will leverage multi-omic data generated from both patient samples and cell lines, to include RNA-seq, whole exome sequencing, multiplex-immunofluorescence, proteomic and lipidomic profiling, and the application of digital and computational pathology to develop and to leverage new multi-omic perspectives to improve breast cancer diagnosis and response to therapy and how they can be used to reduce differences in breast cancer outcome based on race and ethnicity. 

Minimum Skills Required:

• Excel spreadsheet based simple graphing and MYSQL database analysis.
• Familiarity with cloud-based computing.
• Familiarity or ability to use digital pathology analytic platforms described above (including Halo, Visiopharm, Aperio, and QUPATH)
• Interpret histological section of patient breast cancer.
• Interpret immunohistochemical and immunofluorescent staining of human breast cancer
• Perform IHC staning.

Minimum Education Requirements:

•  Ph.D.  or  M.D. equivalent in areas of biochemistry, cancer biology, cell & molecular biology, or related field. Experience with evaluating and interpreting histological preparations of mammalian tissues. This includes experience in the performance of tissue culture and cell-based cell and tissue analysis.

Preferred Qualifications:

• Experience in Immunology

  Familiarity with Halo Software

  Familiarity with  Visiopharm Software

  Familiarity with Leica Image Scope Software

  Familiarity with QUPATH Software

  Experience in Deep Learning Neural Networks program (i.e. Tensor Flow; resnet, etc. )

Hiring Salary Range: 

• Postdoctoral Research Scientist: $68,000 - $72,000

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training.  The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

About Columbia University

Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the university to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.

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