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disease. Key responsibilities Lead and conduct the processing and statistical analysis of large-scale long-read RNA and DNA sequencing, single nuclei RNA sequencing and spatial transcriptomics
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of metabolic pathways essential for biosynthesis and redox balance. We investigate how p53 integrates metabolic cues by functioning as both a sensor and regulator of cellular metabolism. In parallel, we seek
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or more of the following areas as demonstrated through at least one first-author publication: machine learning/computer science, computational biology/bioinformatics, cheminformatics. Individuals should
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experience in one or more of the following areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, metabolism/metabolomics, analytical chemistry/mass
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includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models
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range from cell biological over biochemical to molecular biology and bioinformatics approaches. Collaborations with structural biologists are possible. Your profile Applicants should hold a PhD in
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, sequencing, automation, imaging, and bioprocessing. GBI will also have access to substantial compute resources that can be leveraged to further accelerate progress, including scientific compute, bioinformatics
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for a Postdoctoral Researcher with expertise laboratory methods for ONT (Oxford Nanopore Technologies) long-read sequencing based DNA and RNA analysis and bioinformatic methods relevant to the study of
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resonance imaging (MRI) or focalized X-ray irradiator devices will be a plus. Experience on bioinformatic analyses (WES/WGS, (sc)RNA-Seq, ChIP-Seq, ATAC-Seq, Proteomics, Spatial Transcriptomics) and/or R
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interdisciplinary team. Please keep your eyes open for related positions advertised in parallel to this one. If you see yourself to be qualified for more than one of them, please re-submit your application for each