Translational Cancer Bioinformatics Postdoc

Baylor College of Medicine (BCM); Houston (TX); On-site; USD 52,000 - 70,000; Full time

Job summary

Baylor College of Medicine invites applications for a Postdoctoral Fellow to join a multidisciplinary cancer research team. The role focuses on cancer biology, molecular biology, and bioinformatics, with emphasis on tumor signaling, metabolic reprogramming, immuno-oncology, and therapeutic targets.

The candidate will work on cutting-edge models including PDxs, organoids, and multi-omics datasets. Qualified candidates have an MD or PhD and strong data analysis skills, especially in R and Python,

Qualifications

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.
• Proficiency in R and Python for data analysis is preferred.
• Experience with multi-omics data analysis and integration is desired.
• Ability to develop algorithms for innovative multi-omics studies.

Responsibilities

• Conduct in vitro cancer biology experiments (2D/3D cultures, patient-derived models).
• Perform CRISPR/Cas9 KO and siRNA/shRNA KD in cell lines.
• Analyze multi-omics data including RNA-seq, proteomics, and spatial data.
• Execute molecular assays such as qPCR, Western blot, ELISA, and flow cytometry.
• Support mouse studies: breeding, genotyping, and phenotypic analysis.
• Design and execute in vivo xenograft/PDX studies.
• Collaborate with computational biologists and clinicians on translational outputs.
• Prepare manuscripts, figures, and grant-related materials.

Skills

R

Python

Multi-omics analysis

Bioinformatics

CRISPR

Education

MD or PhD in Basic Science or related

Tools

qPCR

Western blot

Flow cytometry

Job description

Baylor College of Medicine invites applications for a Postdoctoral Fellow to join a multidisciplinary cancer research team. The role focuses on cancer biology, molecular biology, and bioinformatics, with emphasis on tumor signaling, metabolic reprogramming, immuno-oncology, and therapeutic targets.

The candidate will work on cutting-edge models including PDxs, organoids, and multi-omics datasets. Qualified candidates have an MD or PhD and strong data analysis skills, especially in R and Python,