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Generation Testing (Month 4) Integrate static analysis tools (e.g., Semgrep, CodeQL) to assess generated code. Measure vulnerability density (e.g., vulnerabilities per 100 lines of code). Compare improvements
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into a research team with established expertise in software security, program analysis, and AI-driven code intelligence, with a track record of collaboration with leading technology companies and
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will be integrated into a research team with established expertise in software security, program analysis, and AI-driven code intelligence, with a track record of collaboration with leading technology
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and open-source release of training and evaluation pipelines. The selected candidate will be integrated into a research team with established expertise in software security, program analysis, and AI
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and testing of NILM hardware and software (4 weeks) a) Propose a test setup for the NILM module using high-power signals, including equipment list and required instrument software. b) Develop
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| FUNCTIONS The assignee of this research will investigate the design and implementation of a novel software platform aimed at estimating the expected computational costs of deploying different AI models
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of the candidate 2. 50% - Experience in the following areas of research: System testing and evaluation, cryptographic applications, side-channel analysis The evaluation panel assigns a classification to each of
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Computer Science (or close field) with strong foundations in data management, machine learning, and software engineering. Coursework or projects in NLP/LLMs, information retrieval, knowledge graphs/ontologies, data
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Computer Science (or close field) with strong foundations in data management, machine learning, and software engineering. Coursework or projects in NLP/LLMs, information retrieval, knowledge graphs/ontologies, data
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. Candidates who submit their application incorrectly or who do not prove the requirements required in this public notice are excluded from admission. In case of doubt, the evaluation panel may demand any