Faculty Position - Department of Computational Biology
Core
Develop next-generation omics platforms and AI foundation models for pediatric precision medicine, including RNA biology, CRISPR functional genomics, single-cell/spatial omics, and multimodal tissue/cell modeling.
Role type
Faculty (Assistant/Associate/Full Member) in Computational Biology
Builds
Novel computational methods, assay–algorithm co-designed tools, and trustworthy AI systems for clinical genomics and pathology.
Domain
Biomedical research / Pediatric oncology / Computational biology
Deliverable
production ML models
Required skills
Assay–algorithm co-design, foundation model development, multimodal learning, clinical informatics pipelines, trustworthy AI (calibration, uncertainty monitoring), LLM-driven agentic systems
Preferred skills
Experience with regulatory genomics, computational pathology (WSI modeling), clinical NLP, high-performance computing
Technologies
CRISPRi/a, Perturb seq, single-cell omics, spatial omics, metabolomics, immunopeptidomics, WSI, EHR, LLMs
Responsibilities
Pioneer assay–algorithm co-design, lead reproducible and open science initiatives, build foundation models spanning DNA/RNA/protein/imaging/spatial/EHR data, develop agentic AI tools for automated analysis or experiment planning
Seniority
Senior, hands-on IC (Faculty level)