65 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Nature Careers in Denmark
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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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: A Ph.D. in biophysics An Msc in physics. Extensive research experience in soft matter and biophysics. Analytical and programming skills for data analysis and ai-based analysis. Good interpersonal and
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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
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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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information For further information, please contact: Professor Torben Heick Jensen, thj@mbg.au.dk, phone +45 60202705 Application procedure Shortlisting is used. This means that after the deadline
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of Decision Support Systems that translate complex spatial data into actionable conservation strategies. The position is time-limited for 3 years but could be negotiated as a 4-year position with reduced
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by the Center for Pharmaceutical Data Science Education (CPDSE). The project aims to get a better understanding of the release and redistribution of hydrophobic drugs from lipid nanocarriers by using