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questions, advancing deep learning models, or other topics discussed with the PI. We use publicly available and simulated genomic data. Core job duties include: (1) Building computational pipelines
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
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using proteomics. (3) determine differences between DsbA proteins of two model organisms, E. coli and M. smegmatis (4) Establishing termini restraining for inhibitor-protein crystallography in
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conduct research related to creating or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Basic Qualifications Core
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fellow to join the 3D Stem Cell Biology Research Lab (https://www.hashinolab.com ) and study normal and pathological development of the human inner ear using stem cell-derived organoids as a model system
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differences between DsbA proteins of two model organisms, E. coli and M. smegmatis (4) Establishing termini restraining for inhibitor-protein crystallography in collaboration with Prof. Weikai Li. Other general
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pathophysiology of the inner ear using multiple genetic mouse models and a novel human stem cell-derived 3D inner ear organoid model. We study genetically-mediated hair cell and neuronal degeneration in these model
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Informatics, Health Data Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
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related to creating or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Basic Qualifications Core job duties include