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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data
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allocation proposals, conducting machine learning workflows, and developing complete models. Example applications include microscopy image data, cryo-electron microscopy, structural prediction and dynamic
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in multimodal imaging. Experience in machine learning is highly valued. You will support user-driven research projects and develop integrated data workflows spanning light microscopy (confocal, super
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administrators. Each year, we process more than 60,000 samples and generate over 400 Terabases of data. More about our activities and services can be found at: https://www.uu.se/forskning/snpseq and https
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, and manipulation of high-dimensional imaging and mass spectrometry data Experience in designing and maintaining reproducible and scalable analysis workflows Solid foundation in statistics and machine
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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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of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. SciLifeLab SciLifeLab is an academic collaboration between multiple Swedish universities