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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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amplitude analysis and scattering theory, heavy-ion collisions and the properties of hot QCD matter, hadronic probes of beyond-the-Standard-Model physics, and formal developments in lattice QCD. A Ph.D. in
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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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spatial transcriptomics to link molecular signatures with tissue architecture. Develop predictive models for disease diagnosis, prognosis, and therapeutic targeting. Experimental and Analytical Approaches
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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
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disinfection engineering, aerosol science, surface science, and data-driven modeling to address HPAI transmission via air, water, and surfaces. The successful applicant will be expected to play a central