137 data "https:" "https:" "https:" "https:" "U.S" positions at Nature Careers in Denmark
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-free clean-laboratory, two ICP-MS, and TCN dating facilities. https://geo.au.dk/en/research/faciliteter/laboratories/facilities . We also have the largest pool of hydrogeophysical electromagnetic
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Are you experienced in integrating field data and remote sensing data with numerical modelling to quantify interactions within ecosystems? Then apply to the open position as associate professor in
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Tenure-track Assistant and Associate Professorship positions in Algorithms at the Department of M...
, combinatorial optimization, cryptology, data structures, fine-grained complexity, and algorithmic research bridging to ML/AI. Tenure-track Assistant Professorship Position Successful candidates for a tenure-track
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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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structures. You will work closely with computational researchers to gather data, evaluate AI predictions, and design experiments. You will work in a team with 7 PhD-students and 4 postdoctoral researchers and
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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