47 data-"https:" "https:" "https:" "https:" "AALTO UNIVERSITY" research jobs at Aalborg University
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at the University. Youmayobtainfurther professional information from Associate Professor Jakob Zinck Thellufsen, +45 9356 2359, jakobzt@plan.aau.dk. Youcanread more on TECH as a workplacehere Youcanread more on
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experiments, integrating experimental data collected during loaded magnetic resonance imaging scans of the human knee joint with the ex vivo findings. By working with in vivo models, you will contribute
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to the project, uniting experts in battery technology and acoustic signal processing and machine learning. The goal is to harness advanced data science techniques to establish a novel paradigm for online non
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, mechanical and durability testing, and integration with advanced machine learning models. The postdoc will collaborate closely with CEBE’s parallel work packages. Experimental and analytical data generated in
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for large-scale data collection and patient interaction. The position offers a unique opportunity to work at the intersection of biomedical engineering, app development, and health data science in a leading
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the ERC Starting Grant research project “Exploiting Nanopore sequencing to discover what microbes eat (NanoEat)” with the aim to combine state-of-the-art metagenome sequencing with state-of-the-art data
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welcome to contact us. You will find contact persons at the bottom of the jobpost. Further information Read more about our recruitment process here The appointment process at Aalborg University involves a
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advanced modelling, data analysis, and algorithmic development. Your tasks will support our core research focus of mathematical and computational approaches to design and implement solution algorithms, with
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encouraged to apply for the position. Do you have any questions? If you have any questions about the position, you are more than welcome to contact us. For professional information, please contact Associate
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the ERC Starting Grant research project “Exploiting Nanopore sequencing to discover what microbes eat (NanoEat)” with the aim to combine state-of-the-art metagenome sequencing with state-of-the-art data