21 natural-language-processing Postdoctoral positions at Aarhus University in Denmark
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level. In the assessment, emphasis will be placed on experience within the fields of history of natural history, book history, and/or visual epistemology, and an interest in working with materials
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to contact is listed in each position, which can be found here Place of work Place of employment is Aarhus University, and place of work is Department of Mathematics, Faculty of Natural Sciences, Ny Munkegade
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, cryogenics and surface-science tools. You have strong communication and writing skills in English. You are a team player but also do not mind working independently. Who we are/ The Department The Department
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Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment committee
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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Professor Tobias Weidner: weidner@chem.au.dk Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman
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of Chemistry, and the group of Prof. Hobolth at the Department of Mathematics. A second postdoc with expertise in stochastic processes and statistical methods will be part of the project and you are expected
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. Nature Physics20, 970 (2024)). You will also work on expanding our coherent imaging methodology to look at dynamics and phase switching in materials at the nanoscale (Johnson et al. Nature Physics19, 215
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and/or nanofabrication being a plus. Who we are The Department of Physics and Astronomy is a department on Natural Sciences. The main objectives of the Department are to carry out research
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater