📢 Fully funded PhD position in AI foundation models for cancer immunology

Our lab https://lnkd.in/gmgsXEZt

This project will develop and apply artificial intelligence models, including foundation models, to understand cancer and the immune system using large-scale single-cell, spatial and multiomic data, leveraging our resource cellNexus (cellNexus.org).

High-throughput technologies are transforming cancer immunology, but extracting meaningful biological and clinical knowledge from millions of cells across tissues, patients, and disease contexts remains a major challenge. This PhD project will address this challenge by developing scalable AI and machine-learning approaches to model tumour-immune interactions, immune cell states and tissue-specific programmes in cancer.

The successful candidate will work at the interface of:

🤖 AI and machine learning

🧬 cancer immunology

🔬 single-cell and spatial multiomics

💻 computational biology and high-performance data analysis

📦 open-source software and reproducible pipelines

We are looking for a motivated candidate with a background in computational biology, bioinformatics, computer science, statistics, machine learning, or a related quantitative discipline. Experience with Python, single-cell analysis, deep learning, or immunogenomics would be highly valuable.

The student will be embedded in a highly collaborative research environment at SAiGENCI and the University of Adelaide, with opportunities to engage with national and international collaborators, contribute to open-source software, publish high-impact research, and develop expertise in AI-driven cancer immunology.

Please email me with your cover letter and CV, including degrees, projects, publications, and your github profile.