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including bio-informatic processing To have experience with nucleic acid molecular manipulation incl PCR and experience in next generation sequencing -primarily on the illumina platform. To be eager to learn
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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded
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developing new visualisation strategies to aid delineation, as well as developing deep learning methods to enhance photon-counting CT images and better visualise tissue boundaries. The project will also
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to research methods and quantitative methodology. Further information Potential applicants are welcome to contact Professor Tea Trillingsgaard (e-mail [email protected] or +45 26858554) for further information