Postdoc: AI Genomics for Precision Oncology & Immunobiology

University of Pittsburgh, Pittsburgh , Pennsylvania, US; Pittsburgh (Allegheny County); On-site; USD 65,000 - 80,000; Full time

Job summary

University of Pittsburgh's Wang Laboratory, UPMC Hillman Cancer Center, invites applications for a postdoctoral position in computational genomics AI-driven precision oncology and translational cancer biology. The role bridges computational discovery with experimental validation to advance precision oncology in breast and ovarian cancer contexts.

The ideal candidate will work on mechanistic AI frameworks, cancer genetics, and biomarker development, collaborating with oncologists to fast-track

Qualifications

• Ph.D. in bioinformatics, computational biology, computer science, statistics, or a related field.
• Strong programming skills (Python, R, or equivalent).
• Experience with machine learning, multi-omics data analysis, cancer genomics, immunogenomics, or systems biology of transcriptional regulation is highly desirable.

Responsibilities

• Develop and apply AI methods for cancer genomics and precision medicine.
• Characterize structural mutations and modeling their impact on tumor microenvironment and immunotherapy response.
• Develop clinical-grade AI models for predicting therapy responses and integrating regulatory networks.
• Validate computationally predicted targets with in vitro/in vivo studies.

Skills

Python

R

Machine learning

Multi-omics data analysis

Cancer genomics

Immunogenomics

Education

Ph.D. in bioinformatics, computational biology, or related field

Tools

Graph neural networks

Regulon-aware pooling

iGenSig‑AI

Job description

University of Pittsburgh's Wang Laboratory, UPMC Hillman Cancer Center, invites applications for a postdoctoral position in computational genomics AI-driven precision oncology and translational cancer biology. The role bridges computational discovery with experimental validation to advance precision oncology in breast and ovarian cancer contexts.

The ideal candidate will work on mechanistic AI frameworks, cancer genetics, and biomarker development, collaborating with oncologists to fast-track