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that will be affiliated with one of six possible multidisciplinary projects. The ideal postdocs will have expertise in some of the following areas: computational modeling, computational biology, computational
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of millions of lakes worldwide. The successful candidate will create innovative solutions that significantly enhance large-scale environmental simulations and meaningfully advance the modeling of global lake
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spinal cord as a model system. You will engage a systematic strategy to identify these mechanisms by generating innovative mouse genetic strains, identifying embryonic defects and the underlying molecular
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modeling. Experience in cell culture, molecular cloning, and bioinformatics analyses is required. Proficiency in statistics and programming are highly meriting, especially in gene regulatory networks
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evolution, and further to modelling. Investigating transcriptional profile of lncRNA. It can be expression quantification, alternative splicing, start sites properties. Performing AI modeling and developing a
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consequences of mitochondrial dysfunction in patients with inherited disorders and in animal models of mitochondrial pathology. The goal is to uncover novel insights into the role of mitochondria in human
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photoreceptive pathways using mouse as a model system. Methods used in the lab include various in vitro, ex vivo and in vivo approaches, as well as functional and behavioral studies of relevant opsin knockout mice
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systems, or network analysis. Experience with methods for causal inference, or modelling of biological systems is also considered a merit, along with prior work involving large-scale sequencing data such as
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the following responsibilities: Designing and performing experiments to study skin regeneration, inflammation, and fibrosis using human tissue samples and preclinical models. Applying advanced molecular and
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and in vivo model systems, applying multiple omics methods. You will be working with clinical samples, method development and several molecular biology techniques, especially PCR and sequencing as