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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
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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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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several
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immunity through detailed molecular characterization of these disease models. Joanna Rorbach’s lab: Our current research encompasses genetic, structural, and biochemical studies to understand the regulation
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-of-the-art semantic and instance segmentation algorithms for 3D and 4D microtomography data. The project has a particular focus towards analysing fibre-based materials but will also consider other material