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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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systems, integrated sensing and communication, and theoretical modeling of 6G systems Solid mathematical background and significant experience in scientific computing programming (MATLAB, Python, C/C
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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 of neurovascular and neurocognitive changes after radiotherapy of childhood brain tumours, as per May...
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Job Description Are you experienced in WGS data quality control and analysis from bacterial isolates? Do you have a strong interest in genomics and antimicrobial resistance (AMR)? The Research Group for Global Capacity Building (GloCaB) is looking for a dedicated bioinformatician to join our...
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our journey. See our publications and projects here. DTU Compute – Department of Mathematics and Computer Science – is an internationally recognised academic environment with over 400 employees
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developed. You should be highly qualified in: Thermodynamic theories and models for electrolyte solutions Mathematical modelling and computational algorithms Scientific dissemination As a formal qualification
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We are looking for a highly motivated and driven postdoc for a 33-month position to commence on 1 June 2026. The postdoc will be part of the research group Lifecourse Nutrition and Health. Our research The research group Lifecourse Nutrition and Health within the section Nutrition and Health is...
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Compute - Department of Mathematics and Computer Science – is an internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies
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activities, as specified below (“Formalities and salary range”). Place of work Place of employment is Aarhus University, and place of work is Department of Mathematics, Faculty of Natural Sciences, Ny
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, which makes it ideal for ecological simulations where precise mathematical descriptions of key processes are lacking but data for training are available. The MCL methodology will be applied on critical