Shanquisha D. - Postdoctoral Research Fellow – Genomic Medicine Division

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Houston, United States

Experience

Jan 2024 - Present

1 year 11 months

Houston, United States

Postdoctoral Research Fellow – Genomic Medicine Division

MD Anderson Cancer Center

Conducting large-scale RNA-seq and ATAC-seq analyses to identify transcriptional signatures of cancer cell adaptation.
Designed computational pipelines using Python, R, and Seurat for multi-omics integration.
Collaborated with the AI in Oncology group to build benchmark datasets for predictive modeling of tumor evolution.
Co-supervised graduate students and co-authored two manuscripts under peer review.

Jan 2021 - Dec 2023

3 years

Austin, United States

Teaching Assistant – Advanced Molecular Biology (BIO 421)

University of Texas at Austin

Led weekly tutorials and laboratory demonstrations for 60+ students.
Awarded Outstanding Graduate Teaching Award (2022).

Jan 2020 - Dec 2023

4 years

Austin, United States

Graduate Research Assistant – Molecular Oncology Laboratory

The University of Texas at Austin

Led NIH-funded study exploring chromatin accessibility and transcription factor binding in breast cancer models.
Employed CRISPR/Cas9, qPCR, and ChIP-seq to validate oncogenic regulatory networks.
Developed data evaluation protocols ensuring technical reproducibility and clarity for AI-assisted analyses.
Presented findings at the Texas Molecular Biosciences Symposium (2023).

Jan 2019 - Dec 2020

2 years

Undergraduate Mentor – Texas Undergraduate Research Initiative (TURI)

Texas A&M University

Jan 2018 - Dec 2020

3 years

College Station, United States

Research Assistant – Genomics Core Facility

Texas A&M University, College Station

Managed NGS sample preparation and quality control for multi-institutional projects.
Implemented automated workflows in R and Galaxy to improve data throughput by 30%.
Provided bioinformatics support for sequencing-based diagnostic projects.

Summary

Accomplished Molecular and Computational Biologist with a Ph.D. and over 6 years of multidisciplinary research experience.

Expertise in genomics, transcriptomics, and cancer biology, combining experimental molecular work with advanced computational data analysis.

Proven success in developing reproducible datasets, authoring peer-reviewed publications, and mentoring students in molecular biology and data interpretation.

Dedicated to bridging the gap between wet-lab biology and AI-powered scientific discovery.