64 phd-in-mathematical-modelling-of-biochemical-reactions Postdoctoral positions in Belgium
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Integration of phenotypic data with omics analysis Explore machine learning and network analysis methods Profile Essential A PhD in Bioinformatics, Computational Biology, Evolutionary Biology
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temperature signalling in plants, such as the model plant Arabidopsis thaliana and the crop plants wheat and soybean. To unravel this, we focus on dynamic changes in protein phosphorylation status, since
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question: « what makes our brain human ? » (Vanderhaeghen and Polleux, Nat. Rev. Neurosci. 2023). We combine cutting-edge approaches such as pluripotent stem cell models of human corticogenesis, human-mouse
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question: « what makes our brain human ? » (Vanderhaeghen and Polleux, Nat. Rev. Neurosci. 2023). We combine cutting-edge approaches such as pluripotent stem cell models of human corticogenesis, human-mouse
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. Profile You hold a PhD in biomedical sciences, biotechnologies or related disciplines. You have spent at least 12 months of the three years prior to the start date as a postdoctoral scholarship holder
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the context of neurodevelopment and neuroinflammation. Profile You hold a PhD in biomedical sciences, biotechnologies or related disciplines. You have spent at least 12 months of the three years prior
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activities Undertake teaching at undergraduate and/or post graduate level Your profile The successful candidate(s) will have: An outstanding academic record and a PhD with a specialization in European Law
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the PhD candidates in formulating research questions while ensuring that individual projects take into consideration the overarching research questions Investigating the overarching question of general EU
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based