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at the intersection of systems neuroscience and computational modeling. Our lab is broadly interested in Bayesian inference, perception, multisensory integration, spatial navigation, sensorimotor loops, embodied
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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and
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transcriptomics and genomics datasets. The goal is to identify molecular and spatial signatures of disease progression both in human samples and in experimental models of diabetes. Qualifications: PhD in
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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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-based-modelling. This post-doc will be responsible for conducting these tasks. The spatial microsimulation will create maps that cover the pilot areas and show where demand for either social services
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EV in vivo tracking studies, spatial transcriptomics, imaging mass-cytometry, micro-CT imaging and experimental fetal lung models to address key questions in lung development and repair. This position
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) to develop computational models for electric breakdown of gases Job description Electric gas discharges occur in nature, most prominently in air in the form of lightning and its less visible precursors
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about being a Lund University employee Work at Lund University . Work duties and areas of responsibility The candidate will conduct studies on solid tumors using advanced mouse models and human research
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of five scientific groups in the CFN, and supports the Electron Microscopy facility, which is the largest CFN scientific facility. The CFN is acquiring two new customized, ultra-high spatial resolution and
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/benefits-overview . Posting Summary The Rutgers Center for Advanced Infrastructure and Transportation (CAIT) invite applications for a Postdoctoral Associate position in the area of monitoring and modeling