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adapted from traditional application security testing methodologies and fail to account for the specific challenges posed by GenAI. For example, adversarial attack testing, model inversion vulnerabilities
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look into systems in the small and how we can prepare them to withstand and operate safely and securely through accidental faults and targeted cyberattacks and how large scale constellations can achieve
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short-term physiological responses of tree species and modified long-term dynamics of the whole ecosystem. On the other hand, vegetation demography models are numerical tools formulating forest processes
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look into systems in the small and how we can prepare them to withstand and operate safely and securely through accidental faults and targeted cyberattacks and how large scale constellations can achieve
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out by the Doctoral School in Science and Engineering (https://www.uni.lu/research-en/doctoral-education/dsse ) and engage in courses and activities organised by the doctoral training unit FORFUS
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week, of small group teachings and tutorials. The person will benefit from being part of large research group comprising several PhDs and Postdoctoral Researchers working on related topics of Green and
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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Applications, written in English, should include: A detailed CV A list of publications (if any) A motivation letter Previous degrees List of courses with corresponding grades Contact details of 2
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of the MetaProteomeAnalyzer Software A three months secondment at UGENT B. Mesuere is planned to integrate the developed tools A one-month secondment at the Health Inspectorate of the Luxembourg Health Directorate is planned
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suggest any other topic within the overarching project theme. The doctoral candidate will contribute to the teaching of classes ranging from one to three hours per week, of small group teachings and