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single-cell and single-nucleus multi-omics, machine learning/AI, computational biology, and experimental validation to understand cardiovascular disease progression and identify novel therapeutic targets
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combination immunotherapies. Development of NK cell and CAR-NK cell therapies. Building on advances in cellular engineering, we develop and optimize NK cell-based immunotherapies, including chimeric antigen
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artificial intelligence and machine learning (AI/ML) models that predict therapeutic response, identify clinically actionable patient subgroups, and support personalized treatment strategies. Through
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. Programming experience in Python, Matlab, and SQL. Mathematical modeling and data analysis. Machine/Deep learning (e.g. Pytorch, TensorFlow, JAX). City of Hope employees pay is based on the following criteria
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or more statistical or scripting languages, preferably R or MATLAB. Knowledge of survival-based statistical analysis, such as Cox regression and Kaplan-Meier analysis. Working knowledge of machine learning
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machine learning. The successful candidate will develop and apply methods that integrate multimodal molecular and clinical data (genomic, epigenomic, transcriptomic) across serial patient timepoints
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for integration of multi‑omics and clinical datasets to uncover mechanisms of tumor evolution and therapeutic resistance. Developing and applying state‑of‑the‑art artificial intelligence and machine learning (AI/ML
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our translational efforts is the development of mRNA-based therapeutics, particularly in vivo CAR-T/NK/Macrophage technologies and cancer mRNA vaccines, as well as epitranscriptomics-based biomarkers
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experience in working with Linux HPCs · Experience in applying machine learning methods to genomics data analysis · Experience in navigating public databases and genomics data repositories
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of induced pluripotent stem cell-based human disease models 2) Understanding the role of immunity during tumorigenesis as well as disease relapses in order to design novel inhibitors, CAR-T cell therapy and