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Computational Postdoctoral Fellow with a Strong Background in Bioinformatics

The University of Texas MD Anderson Cancer Center
Houston, Texas (US)
Per NIH Guidelines
Closing date
15 Jun 2024

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Health Science
Job Type
Employment - Hours
Full time

UT MD Anderson Cancer Center

Translational Molecular Pathology

Humam Kadara Lab


Program Description:

Our group studies ecological mechanisms in early lung cancer development and response to immune-based treatment (e.g., Sinjab et al, Cancer Discovery, 2021; Hao et al, Cancer Discovery, 2022; Han et al, Nature, 2024). We seek a talented and highly motivated computational postdoctoral fellow with a strong background in bioinformatics and passion in exploring the heterogeneity and evolution of normal, progenitor, and tumor cells as well as the tumor microenvironment (TME) using state-of-the-art single-cell and spatial profiling approaches. The primary research focus of the candidate postdoc will be to employ innovative bioinformatics approaches to dissect in both human-relevant models of lung cancer as well as unique cohorts of human lung tissues the tumor “ecosystem” and profile in-depth phenotypic and functional heterogeneity, lineage plasticity and evolutionary dynamics of tumor and TME cells as well as cell-cell interactions in order to better understand lung cancer development, progression and therapeutic response. The postdoc candidate will work with close collaborators of the Kadara lab at MD Anderson and other institutions. Please check the following link for more information on the Kadara lab:


Learning Objectives:

Learn and master skills for in-depth profiling of single-cell sequencing and spatial transcriptomics data. Learn and master skills for integrative analysis of high-dimensional bulk and single-cell multi-omics data.  Gain rich knowledge in cancer biology, cancer genomics and immunogenomics, and cancer-specific bioinformatics. Develop skills in study design, data interpretation, presentation, and manuscript writing. Develop skills in networking, career planning, teaching, grant writing, and other professional development skills that can help the candidate fellow's career trajectory.


Eligibility & Requirements:

Individuals with a PhD degree in computational biology, bioinformatics, data science or a related field are encouraged to apply. A strong computational background, proficiency in R and at least one additional scripting language (e.g., Python) and knowledge in biostatistics are required. Experience working with single-cell sequencing data and high-performance computing environment is highly preferred. A good understanding of cancer biology, immunology, cell biology, and molecular biology is also preferred. Proven track record of publications, excellent spoken and written communication skills are required. This appointment is not part of a clinical training program; individuals holding an M.D. degree or equivalent are not permitted to engage in patient care activity.


Dates or Training Schedule:

06-01-2024 to 05-31-2026


Stipend aligned with NIH guidelines



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