18 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"INSA-toulouse" PhD positions at University of Twente
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motivated PhD Candidate to strengthen our team. The position aims to use Earth Observation data to improve understanding and modelling capabilities to provide more reliable projections of future fire dynamics
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research prototypes that the community can benefit from. The SCS group is internationally recognized in the broad areas of systems, AI, and data security and is unique for its collaborative and friendly
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of Twente, in close collaboration with the MESA+ Institute for Nanotechnology and clinical and international partners. Information and application You can apply for this position until 31 March 2026 by
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Vacancies PhD Position JUST FUTURES: ReStor(y)ing Multispecies Futures Through Digital Media Key takeaways Your research will engage critically and creatively with environmental data (e.g
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as PhD dissertation. Information and application Please apply by 28 February 2026. The application should include: A Curriculum Vitae; A cover letter For more information regarding the topic
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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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, 2020 . In this PhD project you will work on applying RNPU networks for solving computational problems that are considered hard. Information and application Are you interested in this position? Please
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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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, 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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). 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