63 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Fellowship positions at Indiana University
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experimental systems – from ecosystems to microbiology and developmental biology, from evolution to cell biology, from molecular biology to systems biology, bioinformatics, and genomics. It is always an exciting
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translate these discoveries into precision medicine. We develop computational and statistical methods while integrating human genetics, single-cell and multi-omics, large-scale biobank resources, and
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(AD), mouse models, cell culture or imaging is highly desirable. The postdoctoral fellow will join a multidisciplinary and dynamic research team focused on understanding the role of microglia in
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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
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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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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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of Medicine. In addition to conducting research, the candidate will also be expected to prepare manuscripts, fellowship applications, present findings at internal and external meetings, and help train new grad
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– from ecosystems to microbiology and developmental biology, from evolution to cell biology, from molecular biology to systems biology, bioinformatics, and genomics. It is always an exciting time for
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) Theoretical Modeling: Develop and refine models for entanglement harvesting using continuous-variable quantum information theory and Gaussian quantum states steering. (2) Experimental Simulation: Simulate
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the genetic and developmental basis of pediatric heart disease. We analyze genetic variation in samples from patients with congenital heart defects and utilize mouse, Xenopus and cell-based models to assess