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: Postdoc: Ph.D. in Materials Science, Physics, Chemistry, Mechanical/Electrical Engineering, or related field PhD candidate: Strong Master’s/Diploma degree with very good grades Experience in materials
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deployment Collaborate with interdisciplinary partners and optionally contribute to teaching and supervision Your profile: PhD or strong Master’s degree in computer science, data science, software engineering
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, preferably using yeast Genome engineering / synthetic biology, yeast and/or mammalian Cell biology, microscopy, and biochemical approaches Functional genomics and computational data analysis, including AI
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, preferably using yeast Genome engineering / synthetic biology, yeast and/or mammalian Cell biology, microscopy, and biochemical approaches Functional genomics and computational data analysis, including AI
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/11250664 https://www.jmlr.org/papers/v26/25-1161.html Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in engineering, computer science, or related disciplines (typically
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Skłodowska-Curie Actions (MSCA COFUND). The programme is focused on six research areas, which reflect the scientific pillars of Leibniz-HKI: discovery & engineering of novel antifungals from microbiomes
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group Teaching and Learning with Educational Technology (Prof. Dr. Andreas Lachner) at the Institute of Education. At the heart of the project is the transformation of the re-search group into a trans
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postdoctoral fellows to conduct interdisciplinary research on the interactions between fungal pathogens and microbial ecosystems within the Fellows4Fungi programme at the Leibniz-HKI (Jena, Germany
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extraction, and multi-omics integration workflows. This position is ideal for someone who enjoys working at the interface of technology, instrumentation, and computational modelling, contributing both to data
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funded by the German federal government and 10 percent by the state of Berlin. A fully funded computational postdoctoral position is available in the Spatial Proteomics research group headed by Dr. Fabian