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, epigenomics, single-cell technologies, stem cell biology, muscle biology, aging, immunology, gene and cell therapy, computational analysis, or animal models are especially encouraged to apply. Strong motivation
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or physics Generative AI/transformers, agentic AI, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and Python; best
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the mechanisms of, and interventions for, immuno-senescence and aging in lung transplantation using high-throughput multi-‘omic approaches, primary cell culture systems, and animal models of transplantation. Ph.D
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Summary: Duke University is a world-renowned research institution. Currently, we are looking for a Postdoctoral Associate with expertise in deep learning to participate in a research program focused on
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/time management skills, and interest in interdisciplinary collaboration. • Experience in the use of large language models for analyzing text and/or advanced skills involved in analyzing complex
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of the following tasks: 1) Laser-based instrumentation design, fiber coupling, and optical characterization. 2) Experimental investigation and computational model simulation of laser-induced bubble dynamics and
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application to quantum theory and information science. Other application areas of interest include robust parameter estimation and performance bounds under model misspecification, integrated sensing and
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necessary animal handling for physiological relevance. Collaboration: Working within a multidisciplinary team to integrate structural data with electrophysiology and computational modeling. Choose Duke
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, the Gerber Foundation, and the Burroughs Welcome Fund. This role is for a computational scientist to lead transformer/foundation-model work on FoodSeq data (training, synthetic profile generation, and
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growing portfolio of trauma, critical care, nutrition, ethics, and clinical informatics research. This position will coordinate complex, multi-component studies that include prospective patient enrollment