136 computer-algorithm "https:" "Simons Foundation" positions at Aarhus University in Denmark
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Would you like to facilitate open collaborations that lead to more sustainable and plant-based foods? We are looking for an experienced programme manager for the Plant2Food programme that has been
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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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The Department of Biomedicine, Faculty of Health, Aarhus University invites applications for a postdoctoral position in Computational Spatial Proteomics and Multi-Omics Integration, starting 1
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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Computational Biology (BiRC), Department of Molecular Biology and Genetics (MBG), Aarhus University (http://birc.au.dk), Denmark. The application deadline is 7 April 2026. The position We seek a highly motivated
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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. Science Advances (2024). https://doi.org/10.1126/sciadv.adk1250 Your qualifications: Required qualifications: Applicants must hold a PhD degree in computer science, bioinformatics or similar. The applicant
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medicine. The lab invented the RNA origami method [1] and have developed basic algorithms and software for RNA design. However, there is a great need to develop new software for the design of advanced RNA
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) as well as various other algorithmic methods for data processing and analysis. Current projects within this scope include, but are not limited to: Detection and classification of lesions Segmentation