12 computer-engineering-network "https:" Postdoctoral positions at Aarhus University in Denmark
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international research network and good industrial and professional collaboration. Please refer to Department of Animal and Veterinary Sciences (au.dk) for further information about the department: https
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, extract, and standardise functional information 2. Develop computational tools that integrate evolutionary and functional information using comparative genomics and deep learning approaches 3. Apply
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environmental science, physics, chemistry, mathematics, engineering or similar. You need to demonstrate experience with collaboration and presenting works at international conferences and leading manuscripts
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Foundation, Independent Research Fund Denmark, etc. Sun lab: https://dandrite.au.dk/people/research-groups/sun-group DANDRITE: https://dandrite.au.dk/ PROMEMO: https://promemo.au.dk/ Department: https
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are The Department of Biology (http://bio.au.dk/) provides a framework for research and teaching in all major biological subdisciplines. The department is especially known for its research contribution in biodiversity
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facilities and technologies, situated in close connection to the research environment, and a comprehensive national and international research network and good industrial and professional collaboration. Please
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multidisciplinary and multicultural team. Inclusive and open minded. Who we are Further details about the Software Engineering and Computing Systems Section can be found here: https://ece.au.dk/en/research/key-areas
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The Department of Mechanical and Production Engineering invites applications for a Postdoctoral Researcher position in Circular Design and Business Development. The position is a fixed-term, full
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the opportunity to contribute to an internationally competitive research programme at the interface of proteomics technology development, regulatory protein biology, and cancer research. Expected start date and
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factor analysis. Develop robust, shareable bioinformatics pipelines for epidemio-genomic and phylogenomic analyses using genomic & metagenomic datasets and implement them in high performance computing