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non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar. Responsibilities
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-throughput experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning
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predict molecular subtypes and therapeutic responses. These tools power a precision oncology framework that enables data-driven treatment selection. In parallel, we generate patient-derived 3D
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policy and quality measurement Secondary data analysis using national datasets The experience is intended to prepare candidates for graduate-level training (e.g., MD, PhD, MPH) or careers in
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approximately 10 PhD scientists who assist Yale researchers with all aspects of research computing, including Yale’s High Performance Computing (HPC) clusters with more than 40,000 cores, multiple petabytes of