58 data-"https:"-"https:"-"https:"-"https:"-"Universidade-do-Minho" positions at Nature Careers in Denmark
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Tenure Track Assistant Professor or Associate Professor in building information modelling and dig...
levels. The candidate should have demonstrated expertise in building information modelling (BIM) and building energy modelling (BEM) for detailed design and operation of building enclosure components and
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unified data framework for microbial carbon dioxide conversion, integrating data from methanogens, acetogens, and hybrid projects for standardization, kinetic/thermodynamic measurements, and predictive
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Work The place of work is Ny Munkegade 120, 8000 Aarhus C. Contact Information Further information about the position may be obtained from / For further information please contact: Dr Simon Wall +45
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Aarhus University with related departments. Contact information For further information, please contact: Prof. Anders Bentien, bentien@bce.au.dk, +45 30 36 95 15 Deadline Applications must be received
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the Center for Pharmaceutical Data Science Education (CPDSE) and will be conducted under the supervision of Associate Professor Casper Steinmann . The project concerns physics-based computational modeling
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Research Assistant in Physical Computing and Wearables at the Department of Computer Science, Aar...
research is at the cutting edge of Human-Computer Interaction (HCI), personal fabrication, and physical user interfaces. As a research assistant, you will support our research team on implementing a novel
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. Specifically, the project will combine 30 years of Danish health data at the service of hundreds of women with endometriosis, recruited through online platforms. It will use AI-enhanced methods to handle
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project activities. Key responsibilities include: Investigation into the GEUS sediment archive to extract information on the properties of subglacial sediments deposited by past ice streams. Analysis
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the microbial communities responsible for dark carbon fixation at hadal depth. The focus will be on pelagic communities, but aspects of benthic chemosynthesis could be included. For further information please
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, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer