Postdoctoral Fellow - Dr. Dr. Kasthuri Kannan Lab. - Dept of Translational Molecular Pathology at MDACC

The University of Texas M. D. Anderson Cancer Center

Houston, TX

Job posting number: #7069922

Posted: September 17, 2020

Application Deadline: Open Until Filled

Job Description

Position/Program Description
The Computational Pathology Program (CPP) in the Department of Translational Molecular Pathology is a focused initiative aimed at research and discovery to enable the emerging concepts of precision pathology and medicine using data science and computational algorithms. A major goal of this program is to apply statistical and computational principles to develop novel biomarkers as well as performing image-based data analytics for elucidating biological and clinical variables that underlie cancer mechanisms. CPP strives to identify critical molecular markers, signatures, and mechanisms through appropriate statistical analysis and data integration schemes, including clinical and omics data.
We invite a highly motivated post-doctoral fellow to perform cutting-edge research on the Immune Topographical Atlas of Brain Tumors. The primary focus is on developing a robust spatial statistics portfolio through the application of stochastic processes and analysis of brain tumor images using R/Python, leading to good quality publication(s). The person will need to be able to work as part of a multidisciplinary team involving immunology, pathology, and neurosurgery at MD Anderson Cancer Center while working towards enhancing his/her research portfolio.
Learning Objectives
The position will require learning and applying stochastic processes and algorithms to multiplex brain tumor images to understand and decipher the immune landscape. He/she will be offering creative solutions and are expected to develop good data science skills and solutions in elucidating mechanisms underlying tumor progression in brain cancer with a focus on immune biology.
The postdoc will also be expected to learn to write up the results for weekly meetings, contribute writing to manuscripts, and present findings in institutional and national meetings.
Eligibility Requirements
An individual with a Ph.D. in computational biology with a strong biostatistics background from a good University/Institute (candidates within one year of graduation are also eligible). At least one first author publication in a peer reviewed journal stemming from Ph.D. studies is required. The candidate must have independent thinking and passionate about a career in academic science. Statistical modeling proficiency is a solid plus.
Training Scheduled:
November 2020 - November 2021, renewed annually
Mentor Matching:
This position reports to Dr. Kasthuri Kannan (

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