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for space applications. The project aims to drastically reduce power consumption and data bandwidth while increasing processing speed and dynamic range compared to conventional image sensors. The technology
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barriers and facilitators of prevention programs. The ideal candidate has a background in or experience with one or more of the following topics and areas: Survey methodology / Survey data analysis
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research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and
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. Consequently, your employment will as of that date be with a department. Contact information For further information, please contact: Assistant Professor Emil Laust Kristoffersen, +45 29271306, emillk
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to data from various sensors and radio signals? This is the main underlying theme to be explored within this postdoctoral position. The appointed researcher will investigate how AI embedded in physical
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data storage in Iceland. Drawing on science and technology studies and, specifically, infrastructure studies (Edwards et al 2009; Star 1999), the project aims to follow moments of instability and re
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Aarhus University with related departments. Contact information Before applying or for further information, please contact: Associate Professor Aurelien Dantan, +4523987386, dantan@phys.au.dk . Deadline
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
on “Integrating AI into Aquatic Ecosystem Models to Decode Ecological Complexity” funded by Villum Fonden. Within that project, the focus is on exploring novel ways to infer information from environmental data
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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. We expect applicants to hold a PhD in a relevant field such as techno-anthropology, science and technology studies, human-computer interaction, human-robot interaction, digital health, anthropology