263 machine-learning-and-image-processing Postdoctoral research jobs at Nature Careers
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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of Münster developing imaging methods allowing to visualize molecular processes inside organisms, tissues and cells. With the help of imaging, we perform cutting-edge research in vascular, inflammatory
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responses are affected by the native microenvironment in order to design and engineer natural polymers to support the investigation of these processes in vitro and in vivo. Our research liaises engineering
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(multiomics), CRISPR genome editing, deep learning, network modeling, confocal and two-photon live imaging. Please visit the Özel Lab Website for more information. Ideal candidates will be highly motivated and
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drugs. Areas of interest are: development of in vivo imaging assays for understanding efficacy of novel antifungal drugs, assay development, and determination of resistance liabilities of novel antifungal
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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different physico-chemical environments to drive self-organisation processes, like condensates, that shape mesoscale structures enabling tissue function. As a Postdoctoral Researcher at the Rosalind Franklin
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(data assimilation, machine learning, etc.) Writing proposals / securing external research funding Writing and submitting scientific papers Leading a research group Supervising students Participating in
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The candidate will have a PhD or equivalent degree in bioinformatics, biostatistics, computational biology, machine learning, or related subject areas Prior experience in large-scale data processing and
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processing in the mammalian cochlea in vivo , and how these influence central auditory neuronal pathways. The project will primarily involve using in vivo 2-photon imaging and AAV-gene delivery applied to a