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    Opportunity: Spatial Omics Computational Biology Postdoc -- Precision Medicine @ University of Texas Health San Antonio -- San Antonio, TX (US)
    Submitted by Kumar Sharma; posted on Saturday, September 11, 2021


    The Center for Renal Precision Medicine (CRPM) at the University of Texas Health San Antonio is seeking a dynamic, independent, and creative computational biology postdoctoral researcher or research scientist to join the team. You will develop novel computational methods to integrate Spatial Omics datasets produced in-house as well as publicly available datasets across a range of projects in nephrology, cancer and other metabolic diseases.

    The CRPM, directed by Dr. Kumar Sharma (Vice Chair of Research in Medicine and Division Chief of Nephrology), has recently pioneered breakthrough technical advances in Spatial Metabolomics to unravel mechanisms of disease in nephrology, cancer and metabolic diseases. As a result, you will have the opportunity to build a diverse range of expertise and skill sets from working with cutting-edge technology, and partner in CRPM's extensive national and international collaborative network of leading researchers at prominent institutions across multiple fields and disciplines. Dr. Sharma and the CRPM team are well-recognized in the field and consistently publish in high-impact journals.

    You will apply computational biology techniques and statistical methodologies to analyze and visualize data primarily generated through spatial and bulk metabolomics experiments. You will perform all steps of data analysis including data quality checks, normalization, statistical tests, correction for multiple testing, as well as further downstream analyses such as biochemical and bioenergetic pathway analysis and integrating results from varied experiments. Together with our scientific team, you will work with and improve upon existing data analysis pipelines and be involved in various collaborative projects. The candidate will also collaborate with various wet lab researchers to aid in experimental and statistical design of projects, and in the biological interpretation and integration of the resulting complex data sets. Knowledge of biochemistry and machine learning is highly valued for this position.

    For the right candidate, who is well-organized and motivated, it may be possible for the employee to work remotely from within the US.


    • PhD in Bioinformatics, Biostatistics, Computational Biology, Biochemistry or similar
    • Strong computational skills and knowledge in programming, statistics, biology
    • Experience with statistical analysis and presentation of results using Python and R
    • Understanding of large-scale metabolomics, proteomics and other omics data and placing it in a biological or spatial context
    • Familiarity with biological networks, their analysis and display
    • Knowledge of Biochemistry is a huge plus.
    • Application and validation of machine learning methods to complex data
    • Knowledge of biological network analysis, and experience with visualization tools such as Cytoscape
    • Team player who can thrive working on large collaborative projects
    • US citizen or permanent resident preferred.


    Start Date: Immediate
    Part-time or Full-time possibility


    Apply by sending the following to Blanca Sandoval, Business Manager to Professor Kumar Sharma (sandovalb3[at]
    • Current CV
    • Cover Letter
    • Two Reference Contacts
    We are looking forward to hearing from you!

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