297 data "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" Postdoctoral research jobs in Denmark
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for the optimal candidate later dates may be negotiated. You can read more about career paths at DTU here . Further information For further information about the research at SurfCat at the Department of Physics
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research projects, from initial conception and design through to completion. Communicate research results: presenting data at national and international conferences and meetings, writing reports and
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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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to assess cell performance evolution and degradation behaviour Investigating impurity-induced degradation mechanisms related to feed gases, system components, or cell materials Analysing experimental data and
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the relevant union. The period of employment is 3 years. You can read more about career paths at DTU here . Further information Further information may be obtained from Associate Professor Timothy P. Jenkins
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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