139 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at Aarhus University
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: https://ece.au.dk What we offer The Department of Electrical and Computer Engineering offers: An exciting opportunity to work on cutting-edge research in IoT systems and critical infrastructure monitoring
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computer graphics, or human vision and attention. The posts require research skills in the design of studies, use of methods, research prototyping and data analysis, and you should have documented experience
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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funding The place of work is Langelandsgade 140, 8000 Aarhus C, and the area of employment is the Department of Chemistry, Aarhus University and related departments. Further information about the position
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: Establish and develop experimental protocols and pipelines and implement data management compliance. Presentation of your work in various meetings (locally at the department, national and international
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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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datasets, UAV-derived information on NBS, and environmental data to quantify ecosystem services across Danish agricultural landscapes. The postdoc will work within an interdisciplinary team of applied and
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As research assistant, your primary tasks are full time laboratory work and data analysis. You contribute to the development of the department through research of high international quality. In your
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Department of Electrical and Computer Engineering (ECE), Aarhus University (AU) invites applications for a position as Tenure Track Assistant Professor/Associate Professor in electronics
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dynamics information. As a postdoc, you will contribute to the development of single molecule fluorescence real-time imaging methodologies using both experimental approaches, involving model nucleic acids