Postdoc Openings: Computational Genomics, AI Precision Oncology, Cancer Biology and Immunobiology

Postdoctoral Positions: Computational Genomics · AI-Driven Precision Oncology · Translational Cancer Biology and Immunobiology

Wang Laboratory, UPMC Hillman Cancer Center

Department of Pathology and Human Genetics, University of Pittsburgh

The Opportunity
Two postdoctoral positions are available in the Wang Laboratory at UPMC Hillman Cancer Center, one of the nation’s leading NCI-designated comprehensive cancer centers. We seek highly motivated scientists with expertise in computational genomics/AI and/or translational cancer biology to join our dynamic, well-funded research program at the frontier of cancer genetics and precision oncology.

Candidates with training in both computational genomics and cancer biology are especially welcome to apply —our lab thrives on bridging computational discovery with experimental validation, and dual-skilled scientists will find exceptional opportunities to lead integrative projects spanning both domains.

Our lab operates at the intersection of computational innovation and experimental cancer biology. Funded by over $11.5 million in research grants—including four active DOD Breakthrough Awards totaling $5.1 million—we offer an exceptional environment for ambitious postdoctoral scientists to make high-impact discoveries with direct clinical translational potential.

Why Join Us?

“Dark matter” cancer genetics: Pioneer discoveries in uncharted areas of breast cancer genetics, including recurrent gene fusions (ESR1-CCDC170, BCL2L14-ETV6, RAD51AP1-DYRK4) and intragenic rearrangements (IGRs)—a largely unexplored class of genetic aberrations.

Precision immuno-oncology: Develop next-generation biomarkers (IGR burden, TAA burden, IMPREG signature) for immunotherapy patient selection, especially for TMB-low and PD-L1-negative cancers where current tools fall short.

AI-powered precision oncology: Build mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights.

Translational impact: Work alongside oncologists on a rapid discovery-to-clinic pipeline, with prospective clinical study and clinical trial design directly linked to laboratory findings.

Proven trainee success: Our postdoctoral alumni have received prestigious fellowships from the DOD, Susan G. Komen Foundation, Hillman Cancer Center, and the Gottfried Family Women’s Health Award, totaling over $1.3M in trainee funding.

High-impact publications: Join a track record of publications in Nature Biotechnology, Nature Communications, Science, PNAS, Cancer Discovery, Cancer Research, Cancer Immunology Research, and Clinical Cancer Research.

Position 1: Computational Genomics & AI-Driven Precision Oncology

This position focuses on developing and applying advanced computational and AI methods to tackle major challenges in cancer genomics and precision medicine. Specific areas include:

1) Building the Genomics to Knowledge (G2K) agentic AI framework for automated transformation of multi-omics data into biological insights through iterative, hypothesis-driven computational analysis. 2) Characterizing the landscape of structural mutations—including intragenic rearrangements (IGRs)—across cancer types and modeling their impact on the tumor immune microenvironment and immunotherapy response. 3) Developing clinical-grade mechanism-driven AI models (iGenSig-AI) for predicting responses to targeted therapies and immunotherapies, integrating graph neural networks, regulon-aware pooling, and transfer learning with biological regulatory networks. 4) Developing and validating computational biomarkers (IGR burden, TAA burden, IMPREG signature) for precision immuno-oncology panels.

Preferred 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.

Position 2: Translational Cancer Biology & Immunobiology

This position focuses on the experimental validation and biological characterization of newly discovered genetic targets at the interface of cancer genetics, pathobiology, and immunobiology. Specific areas include:

1) Investigating the functional roles of recurrent gene fusions (ESR1-CCDC170, BCL2L14-ETV6, RAD51AP1-DYRK4) and novel intragenic rearrangements in breast and ovarian cancer progression, immune evasion, and therapy resistance. 2) Characterizing novel structural mutations in actionable kinases and evaluating genotype-directed therapeutic strategies in preclinical models. 3) Performing in vitro and in vivo validation of computationally predicted cancer targets, including studies of epithelial-mesenchymal transition, drug resistance, and immune dysfunction. 4) Exploring immunotherapeutic strategies guided by biomarker status, including combination therapies with β-catenin inhibitors and immune checkpoint blockade in triple-negative breast cancer.

Preferred qualifications: Ph.D. in cancer biology, molecular biology, immunology, genetics, or a related field. Experience with cell and molecular biology techniques, animal models, immunology assays, or translational research. Candidates with combined computational and experimental skills are especially encouraged to apply.

About the Lab & Environment

The Wang Laboratory is a multidisciplinary research group dedicated to discovering novel cancer genetic targets and achieving affordable precision oncology through the integration of computational genomics, machine learning, cancer genetics, and translational cancer biology. We are housed within the UPMC Hillman Cancer Center and the Departments of Pathology and Human Genetics at the University of Pittsburgh School of Medicine, providing access to world-class research facilities, vast clinical sample repositories, comprehensive computational infrastructure, and a vibrant intellectual community spanning clinical and basic sciences.

Postdoctoral trainees will receive unique multidisciplinary mentorship and have opportunities to develop independent research directions, contribute to our translational efforts, and build a competitive portfolio for academic or industry career advancement.

Learn more:

How to Apply

Please submit a single PDF containing your CV, a cover letter describing your research interests and career goals, and the contact information for three references. Review of applications will begin immediately and continue until the positions are filled.

Contact:

Xiaosong (Johnathan) Wang, M.D., Ph.D.

Associate Professor of Pathology and Human Genetics

UPMC Hillman Cancer Center, University of Pittsburgh

Email: View email address on nature.com

Web:

The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity, and diversity. The University offers a comprehensive salary and benefits program.