Single-Cell Genomics Research Track
Research in single-cell biology, transcriptomics, and data-driven discovery.
The track begins with the classical toolkit for transcriptomic analysis, then advances into modern machine learning for cell states, trajectories, and single-cell genomic data.
Apply for the Next CohortProtein Design Research Track
Research in protein structure, molecular modeling, and AI-guided design.
The track begins with the foundations of protein structure and computational modeling, then advances into modern machine learning for folding, docking, and sequence-based design.
Apply for the Next CohortSpatial Omics Research Track
Research in spatial biology, digital pathology, and multi-omic machine learning.
The track begins with the core tools of computational biology and image-based analysis, then advances into modern machine learning for spatial transcriptomics, proteomics, and tissue-level discovery.
Apply for the Next CohortComputational Oncology Research Track
Research in cancer genomics, tumor data analysis, and AI for precision oncology.
The track begins with the classical toolkit of cancer bioinformatics, then advances into modern machine learning for genomics, multimodal tumor data, and precision oncology.
Apply for the Next CohortRegulatory Genomics Research Track
Research in gene regulation, noncoding DNA, and sequence-based deep learning.
The track begins with the foundations of genomics and gene expression analysis, then advances into modern machine learning for regulatory DNA, enhancer logic, and noncoding variant interpretation.
Apply for the Next CohortDrug Design Research Track
Research in molecular design, therapeutics discovery, and AI for drug development.
The track begins with the foundations of chemistry, molecular structure, and computational modeling, then advances into modern machine learning for small molecules, screening, and AI-guided drug discovery.
Apply for the Next Cohort