Postdoc in AI/Cancer Research

A Postdoctoral Position in AI and Cancer Research is available in the laboratory of Dr. Yu-Chiao Chiu at the University of Pittsburgh, within the Department of Medicine (Division of Malignant Hematology/Medical Oncology) and UPMC Hillman Cancer Center. This position is jointly supported by NIH and intramural funding. The successful candidate will engage in bioinformatics research to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, particularly by leveraging large language and vision models, for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics), large textual corpora (e.g., scientific literature), and/or pathologic images.

Our research

The Chiu Lab (https://chiu-lab.org/ ) focuses on developing state-of-the-art multimodal AI models for cancer research. Our recent publications have been recognized by both the cancer research and bioinformatics communities, including in Cancer Research Communications (https://doi.org/10.1158/2767-9764.CRC-25-0030 ; presented and highlighted at the AACR Annual Meeting 2025), Science Advances (https://doi.org/10.1126/sciadv.abh1275 ; highlighted by @NCIgenomics as the #1 favorite paper of the year), Analytical Chemistry (https://doi.org/10.1021/acs.analchem.4c05138 ), and Cancer Letters (https://doi.org/10.1016/j.canlet.2026.218289 ). We are currently supported by active funding from the NIH (NIGMS, NCI, and OD) and various institutional sources.

Candidate qualifications

We seek a highly motivated and enthusiastic individual who meets the following criteria:

• Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related discipline
• Strong experience in integrating several of the following components:
  • Deep learning and LLMs for molecular biology
  • Vision foundation models for pathological image analysis
  • Multi-omics datasets (e.g., TCGA, TARGET, CCLE)
  • Single-cell and spatial transcriptomics/proteomics
  • High-throughput drug and genetic screens (e.g., DepMap, PRISM)
• Common bioinformatics resources and pipelines (e.g., NCBI, Ensembl, BWA, STAR, GATK, VarScan, DESeq)
• Proficiency in Linux and programming languages such as Python, R, MATLAB, or Perl
• Excellent written and verbal communication skills in English, along with a collaborative mindset

Career development opportunities

Dr. Chiu has a strong track record of mentorship, including receipt of the UPMC Hillman Cancer Center Outstanding Research Mentor Award in Clinical/Translational Science and mentorship of the NIH/NCI F30 Predoctoral MD/PhD Fellowship awardee. The selected candidate will receive personalized mentorship in career development planning, preparation of competitive grant and fellowship applications, and access to extensive resources available through the UPMC Hillman Cancer Center (https://hillmanresearch.upmc.edu/training/post-doctoral ). Opportunities for cross-disciplinary collaboration with clinical, translational, and basic scientists will enable the candidate to apply cutting-edge computational approaches to real-world challenges in precision oncology.

How to apply

Interested candidates should apply at: https://cfopitt.taleo.net/careersection/pitt_faculty_external_pd/jobdetail.ftl?job=25002577 (Requisition #25002577). Please submit

• Curriculum vitae (CV)
• One-page summary of research experience and interests
• Contact information for three references

Review of applications will begin immediately and continue on a rolling basis until the position is filled. For inquiries, contact Dr. Yu-Chiao Chiu at YUC250@pitt.edu .

The environment

The University of Pittsburgh School of Medicine ranks #7 in NIH funding in 2025 and is a Tier 1 institution in Best Medical Schools: Research. Pittsburgh is consistently ranked among the most livable cities in the U.S., offering a rich environment for work-life balance. The Chiu Lab fosters a collaborative culture, with access to cutting-edge computational and experimental resources in one of the nation’s top NCI-Designated Comprehensive Cancer Centers.