500 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"SciLifeLab"-"IFM"-"IFM" positions in Denmark
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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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) and fourteen associated partners including six from industry and two start-ups. More information may be found on MICROSUNSET . To be eligible for a MICROSUNSET PhD-position, you must not have lived
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) and fourteen associated partners including six from industry and two start-ups. More information may be found on MICROSUNSET . To be eligible for a MICROSUNSET PhD-position, you must not have lived
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wide variety of services for international researchers and accompanying families, including a relocation service and an AU Expat Partner Programme . You can also find information about the taxation
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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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cell biology, protein chemistry and mass spectrometry, molecular microbiology and biophysics. For further information about the position please contact Professor Brage Storstein Andresen, PhD, FRCPath, e
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on real-life data from the maritime industry. As part of the PhD, you will be following advanced courses to extend your skills, implement and test algorithms, and learn to write scientific papers. As part
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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