247 data "https:" "https:" "https:" "https:" "University of St" PhD positions in Netherlands
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, fundamental research and/or studies involving matters of scientific urgency. Information and application Are you interested in this position? Please send your application via the 'Apply now' button below before
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University is looking for a Research Assistant to join the multidisciplinary team at the Donders Institute. The study involves organising acquisition of behavioural and neuroimaging (fMRI) data from six-year
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surveys and field experiments Ability to organise data collection Proactive in engagement with stakeholders and local communities, and setting up collaborations and on-site research activities We look for
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to what extent data poisoning attacks can influence the output of LLM models in security and safety critical infrastructure. 3. Perform the attack under different scenarios and model the impact. 4. Evaluate
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, exposing the limitations of current detection timelines. This reactive posture is worsened by a visibility gap in the DNS ecosystem. A lack of transparency in registration data, coupled with the short-lived
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approach that combines semantic material data, design-for-circularity, and hub logistics to scale high-quality reuse in regional infrastructure ecosystems (primary focus: Twente; validation: Brabant). Reuse
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Investigator (PI), Dr Marzi. Together, you will further develop and refine the PhD case studies, the research approach and the various work packages, as well as analyse data, participate in conferences and
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Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University . About us A better future for
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future of sustainable materials and technologies! Information and application Are you interested? Send your application before March 31, 2026 via the provide button and should include: Personal motivation
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will