566 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions in Austria
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qualifications and experience. APPLICATION We look forward to receiving your application. Please apply online at https://www.kl.ac.at/en/university/career-kl , quoting reference number “2605”, by 31th March 2026
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the PhD should be within the areas of expertice of the laboratory for Cognitive Research in Art History (https://crea.univie.ac.at/). Your future tasks: PhD thesis, preferably in the area of the FWF
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: https://jobs.tuwien.ac.at/Job/262872 Where to apply Website https://jobs.tuwien.ac.at/Job/262872 Requirements Research FieldGeosciences » OtherEducation LevelPhD or equivalent LanguagesGERMANLevelGood
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whose research addresses migration and its interrelations with human capital formation. Applicants should be able to teach all the main areas of demography from an international perspective and
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| Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.03.2030 Reference no.: 5335 Among the many good reasons to want to research and teach
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the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists
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at the University of Vienna and integrated into the Gravitational Physics group (https://gravity.univie.ac.at/), an active research unit engaged in fundamental theoretical questions of gravitation. The group includes
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: https://ie.univie.ac.at/en/ Your academic profile: Doctoral degree/PhD Two years of international research experience during or after doctoral studies Outstanding research achievements, excellent
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skills, including proficiency in statistics, scientific programming, and/or modelling. We especially welcome candidates interested in applying AI and machine learning to analyse heritage datasets
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statistics, scientific programming, and/or modelling. We especially welcome candidates interested in applying AI and machine learning to analyse heritage datasets. What we offer: • A stimulating