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imaging technologies, behavioral neuroscience approaches, molecular techniques, and data analytics to answer important scientific questions and advance translational discoveries. What You'll Do: Lead
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work at the intersection of systems neuroscience, neurophysiology, imaging, and computational analysis to uncover how motor cortical circuits support learning and memory. Be You. You will contribute
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proteostasis, cytoskeletal dynamics, and ferroptotic cell death. This collaborative work combines biochemistry, chemical biology, cell signaling, live-cell imaging, and organotypic brain slice models to dissect
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the cellular crosstalk and basic molecular mechanisms during lung repair and disease. We utilize in vivo mouse genetics, live -imaging, 3D organoids, functional screening, and next generation sequencing
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, genomics, or computational analysis of high-dimensional datasets. Experience with one or more of the following: Flow cytometry Single-cell sequencing Spatial transcriptomics Multiplex imaging Bioinformatics
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development of machine learning tools and their applications to medical imaging. Key Responsibilities: The Post Doctoral Associate will apply their technical skills toward the development, implementation, and
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acquire new technical expertise as needed. Participate in clinical research efforts involving retrieval, processing, and molecular analysis of patient-derived specimens from prospective clinical trials
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, neuroinflammation, tau and α-synuclein pathobiology, digital pathology/AI image analysis, and mouse models of neurodegeneration. Education: A recent Ph.D. (less than 2 years of postdoctoral experience is strongly
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-edge technologies, including genetically engineered mouse models, patient-derived models, single-cell and spatial genomics, organoid systems, and preclinical therapeutic studies. Learn more about our
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/ estimation / SAR imaging / STAP, cognitive radar / sonar, communications over dynamic channels, orthogonal time frequency space (OTFS) modulation, shared-spectrum / RF convergence, machine and deep learning