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supported by more junior colleagues (PhD candidates, Bachelor’s and Master’s students). Requirements PhD degree in Computational biology or related (Computer Science, Physics) Experience with NGS data
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students). Requirements * PhD degree in Computational biology or related (Computer Science, Physics) or at least 3 years of experience in scientific software development * Experience with NGS data processing
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. Requirements PhD or postdoc experience in bioinformatics, computational biology, or computer science. Strong understanding of genomics and transcriptomics data analysis methodologies and techniques. Hands
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. The working group "Molecular Modeling" at Leibniz-LSB@TUM is looking for a PhD student to start on 01/04/2024 The Leibniz Institute for Food Systems Biology at the Technical University of Munich (Leibniz-LSB
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. The working group "Molecular Modeling" at Leibniz-LSB@TUM is looking for a PhD student to start on 01/05/2024. The Leibniz Institute for Food Systems Biology at the Technical University of Munich (Leibniz-LSB
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(NFDI) initiative and is the German node for the federated European Genome-Phenome Archive (fEGA). The Munich-based GHGA team is hosted by the chair of Computational Molecular Medicine (CMM ), which is
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inflammation, a major human non-communicable disease constantly on the rise, by shaping Treg development, identity and functionality. Your profile - University degree (M.Sc.) in Immunology, Biology, Molecular
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from the Global South. Your profile - PhD degree in Biology, Biochemistry, Molecular Biotechnology with outstanding result in the field of basic and/or translational immunology - Intense knowledge
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equivalent degree in biology, agricultural biology or any related field. • You have a very strong background in cell biology, molecular plant nutrition and / or molecular plant physiology. • You have an
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Master’s degree in biotechnology, bioengineering, bioeconomy cell biology, molecular biology, or a comparable field of study, preferably with a background in life cycle assessment (LCA) and techno-economic