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techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical
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technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human
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MB per file. In case you have more than one file per field you need to combine the pdf-files into a single file, as each field handles only one file. We do not accept zip-files, jpg or other image
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engineering, with a strong willingness to learn the complementary skill set. Experience in collaborative research environments. Excellent communication and teamwork skills. A proactive attitude towards learning
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, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
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areas will be considered an advantage: Confocal microscopy Image processing Optical bench instrumentation – set up and alignment Scientific software development Thermochronology and exposure dating
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hands-on experience in tissue handling, histology, microscopy, and spatial transcriptomics. Experience with the computational analysis of NGS- or imaging-based spatial transcriptomics and single-cell
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of the areas listed on the page above are of interest to you. The list includes positions covering Operator Algebras, Machine Learning, Analytic Number Theory, Automorphic Forms and Representation Theory
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, you will be asked to indicate, which of the areas listed on the page above are of interest to you. The list includes positions covering Operator Algebras, Machine Learning, Analytic Number Theory
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Post Doctoral Researcher in Digital Twins CO2-to-Protein production in collaboration between the ...
collaboration between the Department of Electrical and Computer Engineering and the Novo Nordisk Foundation CO2 research center, Aarhus University, we aim to address this opportunity by developing digital twins