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Aarhus University, Department of Mathematics Position ID: MATHAU-POSTDOC3 [#28128] Position Title: Position Type: Postdoctoral Position Location: Aarhus, 8000, Denmark [map ] Subject Areas: Beyond
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The Department of Mathematics at Aarhus University , Denmark, a top 100 university, is seeking top early-career researchers for a number of attractive 3-year postdoctoral positions within
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The Department of Mathematics at Aarhus University , Denmark, a top 100 university, is seeking a top early-career researcher for an attractive 3-year postdoctoral position within Mathematics
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The Department of Mathematics at Aarhus University , Denmark, a top 100 university, is seeking a top early-career researcher for an attractive 3-year postdoctoral position within Mathematics
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use the algorithms in practice, when little to no assumptions can be made on the data. Required Qualifications PhD in computer science, mathematics, statistics, or related fields (by the start date
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Salary Details The starting salary for a Postdoctoral Research Associate will be from £34,610 on Grade (E), depending on qualifications and experience. The starting salary for a Postdoctoral Research Fellow will be from £43,482 on Grade (F), depending on qualifications and experience. This new...
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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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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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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