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taken a prominent role in international collaborations such as CETAF, DiSSCo, GBIF, FishBase, and CBOL. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence
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Do you want to contribute to top quality medical research? Computational methods and AI applied to large-scale molecular data are transforming biology – from molecular structures and cellular
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developing computational methods, analyzing complex datasets, and contributing to integrative omics efforts in close collaboration with researchers from various disciplines. The roles offer significant
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fellow in data-driven cell and molecular biology. For more information about us, please visit: DBB and MBW Data-driven life science (DDLS) uses data, computational methods and artificial intelligence
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degree in bioinformatics, data science, computer science, scientific computing, or associated field Documented experience with AI methods for analysis of tabular dataset and image-based data including deep
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are service-orientated, proactive, thorough and able to quickly find solutions to questions and problems. You enjoy managing multiple tasks in parallel and working independently, efficiently and in a
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microscopy (EM) method development using focused ion beam (FIB), cryo-EM and electron tomography. The position is for four years of doctoral studies, including participation in research and postgraduate
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application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Your tasks will include conducting independent research in the subject area at
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. Project description: DDLS Fellows Program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Work duties The