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hub in the context of metabolic diseases, such as MASLD and cardiovascular diseases. For this, we apply a range of single cell genomics technologies on clinical biopsies combined with bioinformatics
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experiments as well as bioinformatics and advanced imaging techniques. Your core tasks are: Cloning and expressing recombinant proteins. Developing and optimizing purification protocols. Designing and
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isolate and functionally characterize natural product biosynthetic gene clusters via a combination of bioinformatic tools, genetic engineering and chemical analyses. Candidate’s profile: Master’s degree in
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wide spectrum of genetic, molecular, and cell biology, biochemical as well as micobial and bioinformatics techniques to study translational aspects of colon cancer (e.g., Cre/loxP and Flp/FRT-based dual
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PhD fellowship at the Copenhagen Center for Glycocalyx Research at the Department of Cellular and Mo
data science, bioinformatics, protein design, biochemistry, mass spectrometry, cell biology, molecular biology, genetic engineering, medicine or related fields. The successful candidate will join a
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for their own academic further qualification What we are looking for You hold a degree in biology, (molecular) medicine, bioinformatics, or a related field You have experience independently conducting basic
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. We seek outstanding candidates with a Ph.D. in Computational Biology/Bioinformatics, Cell Biology, or related fields. The ideal candidate will have demonstrated expertise in computational analysis
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. Skills and personal qualities Qualifications: The successful candidate should hold a Master’s degree in bioinformatics, computational biology, computer science, engineering, or a related quantitative field
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technologies in genomics, proteomics, bioinformatics, imaging, and more We are housed in the heart of Barcelona, with our science having privileged views over the Mediterranean Sea. Students enjoy a lively
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block within this process. You will be embedded both within an experimental and computational team, providing a unique atmosphere where there is expertise to develop the deep-learning models while having