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edge tools including viral barcoding as well as transcriptomics. Your main role will be to establish a protocol that allows precise virus injections into the early (first postnatal month) mouse brain
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original research in transcriptomics and/or computational biology, and acquire the required experimental and computational skills necessary for the completion of the project. You are expected to communicate
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. liver biology and/or metabolic syndrome or similar Experience in liver biology modelling research, MAFLD and 3D primary hepatocyte NPC spheroid generation and culture Working knowledge on either human and
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mission For this, you will overall organise the data and metadata for the Consortium. You keep regular contact to the DoGA principal investigators and participate in consortium groups, organise and update
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science and with an interest in learning new techniques. You should have a master's degree or an engineering degree, for example in biomedicine or physics. What do we offer? A creative and inspiring
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considered for this position you should: Have completed a bachelor's or master's degree in biology/biomedical sciences/ Biomedical Laboratory Science or basic medical training Have at least 6 months laboratory
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documented experience in the following areas: Masters degree in machine learning and statistics Analyzes of bulk and scRNA-seq data Identification of drug targets In addition, experience in the following area
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experimental and computational approaches for the completion of the project, including microscopy, biochemistry, NGS, proteomics and bioinformatics. The candidate will perform original research in genomics and
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have a master’s degree or equivalent. Experience with cell culture and basic molecular biology tools, such as PCR and cloning, is a requirement. Experiences working with primary immune cell cultures from
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Professor Ioannis Parodis. The main focus of the successful candidate will be to validate the novel SLE-associated autoantigens recently identified by the group, and tasks include development of serological