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: D1. Skills in animal models Experience Essential: E1. Proven ability to deliver quality outputs (such as publications) in a timely and efficient manner. E2. Experience preparing data for publication
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using cellular and animal models, validation of the clinical relevance of these findings using multi-omics datasets in established human cohorts, and exploration of upcycling strategies to develop health
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expected. Excellent knowledge in dealing with complex statistical models and methods and the willingness to support the team in statistical questions are also expected. The candidate should have teaching
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. The technologies include fuel cells, electrolysis, power-to-x, batteries, and carbon capture. The research is based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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skills such as structural equation modeling, multilevel modeling, longitudinal data analysis, and/or categorical analysis (e.g., growth mixture modeling) using R, Mplus, and/or SAS. Preferred
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health and well-being, cognitive aging and dementia, loneliness and social isolation, and integrative data analysis. Strong analytic skills such as structural equation modeling, multilevel modeling
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understanding the molecular basis of retinoid metabolism and signaling. Experience in animal models of lung injury, lung cell isolation, lung organoid cultures, immunofluorescent staining of tissues and cells
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other disease models that are valuable in studying the etiology and treatment for these devastating diseases. We combine in vivo, ex vivo, and in vitro methods to study the pathogenic mechanisms in a
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target all causal microorganisms. An integrated approach that quantifies sour rot disease risk based on within-vineyard environmental and management conditions is necessary. The successful candidate will