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used to reach this goal. These techniques include, but are not limited to, advanced molecular biology, flow cytometry, fluorescence microscopy, cell culture, high-throughput screening and genetic
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, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation group. Main responsibilities Conduct research in collaboration with senior researchers and
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, regulation of neuronal signaling and anti-cancer immunity. Using a combination of cell biology, structural biology and chemical genetic approaches, we have elucidated fundamental mechanisms underlying
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. The successful candidate will employ advanced fluorescence microscopy on eukaryotic cells, alongside a diverse toolkit of genetic engineering and in vitro biochemical approaches, to push the boundaries of our
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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project to study genetic regulatory variation and its link to molecular, cellular and organismal phenotypes using a systems genetics approach. The project is fully computational, and potential approaches
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computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher to contribute to our ambitious mission. Division The Division of Biomolecular and
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function is directed by the genetic material, and how it interacts with various kinds of micro-organisms. Using this knowledge, we try to elucidate the causes of diseases, and find new ways to diagnose and
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specialized knowledge in cardiovascular genetics and bioinformatics skills relevant to the analysis of microRNA and sequencing data. More information about the position The appointment is a full-time, fixed