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scientific developments. Dedicated support from highly skilled specialists in bioinformatics and statistics, helping you strengthen your research with cutting-edge analytical approaches. Access to state
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imaging. A successful postdoctoral candidate should have a Ph.D. in the relevant field with a strong background in LC-MS/MS. Some bioinformatics expertise is preferred but not required. More details about
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. The computational work includes, for example, the analysis of omics data and computational modeling. Experience in cell culture, molecular cloning, and bioinformatics analyses is required. Proficiency in statistics
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, innate immunity RNA Bioinformatics & High-Throughput Methods (Hyeshik Chang): mRNA vaccine design, RNA sequencing, RNA modification analysis RNA–Protein Interactomics (Jong-Seo Kim): proteomics
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Postdoctoral Research Associate - Human Organoid/Assembloid Models of Schizophrenia-associated Risks
shared resources, including the following: An integrated support structure for brain organoids In vivo and ex vivo cellular imaging platforms Bioinformatics support Production of genetically engineered
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in a dry lab setting and will involve analyzing newly generated and publicly available genomic datasets. We will use both in-house and published bioinformatic tools, including phylogenetics and methods
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linked bioinformatics analysis Collaborate with international partners to achieve research goals Prepare manuscripts for publication in peer-reviewed journals Present research findings at national and
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specialized departmental shared resources, including an integrated support structure for rodent behavior testing, brain organoids, in vivo and ex vivo cellular imaging, bioinformatics, production of genetically
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research on the topic outlined above is paramount Candidates are expected to be interested in working at the boundaries of several research domains PhD degree in computational biology, bioinformatics
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physiological balance. Perform LC/MS based proteomic analyses of circulating proteins and assess their impact on organs in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic