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resonance energy transfer, siRNA mediated gene knock out, cellular imaging, qPCR, etc.) to elucidate unknown interactions between GPCRs and receptor tyrosine kinases at the cellular level. Analyses will focus
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within the Clusters of Excellence ‘Machine Learning for Science’ and ‘Image-Guided and Functionally Instructed Tumor Therapies (iFIT)’. Requirements PhD in Bioinformatics, Computational Biology, or a
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-of-the-art transgenic mouse models and imaging technologies to determine how cardiovascular risk genes control the pathological behavior of vascular smooth muscle cells in atherosclerotic lesions. The PhD
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coding skills, experience in managing and development of software projects is a plus Your application Please send your application (including a motivation letter, your CV, up to two representative