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Field
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requirements Master’s degree/subject at second degree level (120 credits/ECTS) in pharmacy, biomedicine, bioinformatics or similar. In order to gain admission to the PhD programme at the Faculty of Health
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techniques including confocal microscopy, bioinformatics and infection assays in CL2 facilities. Main duties: Generate, maintain and characterise organoid and macrophage culture systems. Design, implementation
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of relevant bioinformatics from laboratory work In order to gain admission to PhD programmes at the Faculty of Health Sciences, applicants must have achieved a grade of B or better in their master’s thesis
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relevant field (e.g. bioinformatics, genetics, molecular biology) Proven programming skills (preferably Python, other languages also appreciated) A strong background in biology Strong interest in molecular
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Desirable experience and skills: Experience with bioinformatics FELASA certification for mouse experimental work Interest in evolutionary biology You have an interest in symbiotic microorganisms About Globe
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Biology, Biostatistics, Bioinformatics, Computer Science, Data Science, or related discipline. * At least 1 year of experience in bioinformatics research. * Quantitative training with good understanding
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, translation studies, RNA-seq, and/or applicable bioinformatics is considered an advantage. Furthermore, successful applicants are expected to be competitive in national and international funding schemes. Good
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in additional aspects of biology, bioinformatics and genomics required for successful completion of the programme. The ability to work as part of a team, an interest in industrially focused research
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, genomics, bioinformatics, microscopy, NMR, X-ray crystallography, cryo-EM, flow cytometry, metabolomics, lipidomics and proteomics are readily available on campus. Substantial resources for field-based
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vivo human tissue studies and in vivo rodent modeling. Expertise in human genomics, biology of neuronal and glial cell types, and computational and bioinformatic skills required for genomics data