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amine-based CO2 capture plants. This position at the Department of Chemical Engineering at NTNU focuses on chemical absorption and, more specifically, on the modelling of solvent degradation. Carbon
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The fellowship period is three years. The PhD candidate will work on the project entitled "Male Reproductive Disorders of Foetal origin – Development of an Organoid Model for Mechanistic Insight". Foetal life is a
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of environmental modulation on gametic and early developmental epigenome and epitranscriptome. The project uses next- and third-generation sequencing technologies to generate the data. Zebrafish is a model organism
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explanation at the molecular level. The candidate will be located in Norway, Bodø and have at least one research stay at the Roscoff Research station in France. The KELP-SHIELD project ‘Sugar Kelp Priming
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tasks for the position The candidate will pursue research on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of molecular data in cancer
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Processing or a related field. A background in quantum mechanics and molecular dynamics studies as well as interest in multilevel molecular modelling techniques. Your education must correspond to a five-year
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Analysis: Utilize various cell and molecular biology techniques, including histology, microscopy, flow cytometry, RNA-seq, proteomics, Western blot, and qPCR, to analyze organoid and mouse models
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” recruiting 10 Doctoral Candidates (DCs). The doctoral candidates will be hired in one of the following institutions: European Molecular Biology Laboratory (2), Gulbenkian Institute for Molecular Medicine (1
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Haapaniemi group, located at NCMBM (Norwegian Centre for Molecular Biociences and Medicine) in University of Oslo & Oslo University hospital. The aim of the Haapaniemi group (www.haapaniemilab.org ) is to
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organismal level. Using salmon as the model, the studies will employ primary cells and established cell lines to uncover the functional potential of algal compounds. This will be achieved through in-depth