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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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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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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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developing data processing pipelines, such as Nextflow or similar systems. Computer clusters and distributed systems. Virtual environments, e.g., Docker or Apptainer. Methods for software deployment (e.g
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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
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providers across the country to perform advanced genome and transcriptome analyses based on large-scale DNA sequencing, while also continuously developing methods and pipelines. Our goal is to ensure world
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life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health