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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
models. We focus on creating organoids with precise cell types, architecture, and functions that closely mirror their in vivo counterparts. Our mission is to harness these advanced models to unravel
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18.10.2022, Wissenschaftliches Personal The lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is looking for a Post-Doc. The task will be the multi-modal modeling of medical data
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the following directions: 1) Developing computational methods for integrating multi-modal data, such as scRNA-seq, scATAC-seq, spatial transcriptomics, ChIP-seq, and CRISPR screening. 2) Investigating context
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fundamental tectonic processes governing the behavior of convergent margins across various spatial and temporal scales. To enrich our team, we are currently seeking a motivated candidate in the broadly defined
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space through spatial ‘omics approaches. Responsibilities and qualifications The successful candidate should be eager to pursue ambitious research questions using latest-technology workflows and chart new
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cell-derived embryo models would be desirable. Experience with advanced imaging techniques. Experience with single-cell transcriptomics. Familiarity with multi-omics techniques, spatial analysis
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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the supervision of Dr. Joseph Kwon. We’re seeking a creative Postdoctoral Scholar to join our team and advance cutting-edge multiscale and hybrid modeling—integrating first-principles simulations with
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Spatial Temporality in Education Critical & Embodied Theories Qualitative Research Methods Oral History Critical Policy Analysis Candidates must have documented experience teaching the following courses
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the following responsibilities: Designing and performing experiments to study skin regeneration, inflammation, and fibrosis using human tissue samples and preclinical models. Applying advanced molecular and