1,326 computer-security-"https:"-"https:"-"https:"-"https:"-"Robert-Gordon-University" PhD positions
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- and transdisciplinary research community and training programme; professional command of both English and Dutch; demonstrated skills in quantitative and qualitative research methods, or—where experience
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At the Faculty of Medicine, Department of Health Science and Technology a PhD stipend is available within the general research programme: Biomedical Engineering and Neuroscience. The stipend is open
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Environments within the general study programme Electrical and Electronic Engineering; as per March 1, 2026, or as soon as possible thereafter. The candidate will be based in Aalborg at the Automation and
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in the mandatory PhD research education program Conduct independent research and publish the result in recognised scientific journals and present them at international conferences Participate in
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(or equivalent score) both for the programme in total and the master’s thesis See admission requirements: PhD in Science of Professions It is assumed that the person who is hired is admitted to the faculty’s
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Application deadline: All year round Research theme: Applied Mathematics, Computational Metallurgy UK only This 3.5-year PhD project is fully funded and home students are eligible to apply
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of Ministerial Order No. 1124 of September 19, 2025 on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions. According to the Ministerial Order, the progress of the PhD
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after login redirects. Utløpsdato: Session Navn: .return-state Leverandør: .jobbnorge.no Databehandlingsansvarlig: Fingerprint JS Formål: Device fingerprinting for security purposes Personvernregler
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At Aalborg University (AAU), Faculty of Engineering and Science, Department of Chemistry and Bioscience, an Integrated PhD stipend is available within the PhD study program of Biotechnology
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap