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on post-training methods for these low-resourced languages, for example, by investigating the role of synthetic data, among other data augmentation techniques, and the role of in-context learning in
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date and duration of employment This is a 2–year position from 1 December 2025 or as soon possible. Job description You will be contributing to a collaborative project with industrial partners
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collaborate with PhD and other post doctoral fellows, in cross-disciplinary collaborations with other research groups both national and international as well as with industrial partners. Qualifications A PhD
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-mortem and fractographic analysis Collaborating with colleagues at DTU Energy and industrial partners to improve the reliability of SOEC stacks Publishing your research results in relevant peer-reviewed
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multidisciplinary team will work in close collaboration with the Francavilla-led team at the University of Manchester, UK, and with several scientists with diverse background in Denmark and abroad. Dr Schoof’s team
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. The research will bridge both established and emerging technical expertise within the section, encompassing areas such as FPGA and neuromorphic computing, Edge AI, machine learning, power electronics, and self
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multidisciplinary team will work in close collaboration with the Francavilla-led team at the University of Manchester, UK, and with several scientists with diverse background in Denmark and abroad. Dr Schoof’s team
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provide assistance in organising workshops and advisory board meetings. The post is for two years and represents an exciting opportunity to acquire valuable research experience, to contribute
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, feasibility studies, field experiment etc.) and in organizing collaboration with stakeholders (e.g. end-users, software developer). Furthermore, the successful applicant will be involved in writing up research
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– and is characterized by many international collaborations with other high-ranking universities and research institutions around the world. What we offer The department/centre offers: a well-developed