Job Summary
The primary research focus will be to elucidate the mechanisms underlying fibroblast transition into distinct cancer-associated fibroblast subtypes and their role in regulating epithelial plasticity, immune responses, tumor progression, and therapy resistance.
This work integrates cutting-edge spatial transcriptomics, advanced co-culture organoid assays, and in vivo models to decode the dynamics of cancer-associated fibroblast-driven colorectal cancer evolution.
The individual will apply innovative bioinformatics approaches to human-relevant models and unique patient-derived tissue cohorts from colorectal cancer.
The goal is to comprehensively profile the phenotypic and functional heterogeneity, lineage plasticity, and evolutionary dynamics of epithelial cells, cancer-associated fibroblasts, and immune cells within the tumor ecosystem.
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Key Responsibilities
Apply innovative bioinformatics approaches to dissect the complex interactions between epithelial cells, cancer-associated fibroblasts, and immune cells within the tumor microenvironment.
Integrate spatial transcriptomics, advanced co-culture organoid assays, and in vivo models to decode the mechanisms underlying cancer-associated fibroblast-driven colorectal cancer evolution.
Analyze and interpret large datasets generated from spatial transcriptomics, co-culture organoid assays, and in vivo models to identify key drivers of cancer-associated fibroblast function.
Publish research findings in top-tier scientific journals and present at international conferences.
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Requirements
* Bachelor's degree in Bioinformatics, Computer Science, or a related field.
* Strong background in programming languages such as Python, R, or MATLAB.
* Experience with next-generation sequencing data analysis, spatial transcriptomics, and co-culture organoid assays.
* Excellent analytical, problem-solving, and communication skills.