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The Department of Clinical Medicine at Faculty of Health at Aarhus University invites applications for a postdoc position in the field of medical physics, within the topic image-based analysis
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from large digital data sets to physical samples. Your focus will be to structure and implement data management and storage solutions that can accommodate the various needs in different sub-fields as
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the systems-level plasticity of pure cultures of acetogens upon physical-chemical perturbations during syngas fermentation. This project involves detailed mechanistic and systems-level studies including, but
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although the application process can be completed in the Aarhus University application system without uploading publications or a teaching portfolio, applications that do not include uploaded publications
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of publications. Please note that while the application process can be completed on the Aarhus University system without uploading publications, applications that do not include uploaded publications (a maximum of
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, physics, computer science, applied mathematics, or similar Required competences Strong background in image processing and analysis, especially Deformable image registration and 3D segmentation methods
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. Further information on the tenure review process is provided below. The position will begin on 1 December 2026 or as soon as possible thereafter. The School of Communication and Culture is committed
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. The postdoctoral researcher will collaborate closely with an engineering team responsible for process integration and prototype development Expected start date and duration of employment This is a 2.5–year position
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for the tenure review criteria and for the tenure review process. Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment
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decomposed into modular sub-components that can be either process-based models and/or deep learning models. MCL has the flexibility to replace any uncertain process description with a deep learning model