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existing vulnerability-mining tooling to ensure precise commit-level alignment and reproducibility. 2. Formalization and Extension of Security-Preserving Perturbations (Month 2-3) - Collect/define and
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building automated systems or ML pipelines – 15% Demonstrated experience implementing structured, scalable, or automated software systems. Evidence of experience with neural networks, LLMs, or training
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(Month 3-4) Define robustness metrics for security classification consistency. Evaluate resilience to obfuscation, control-flow changes, and API variations. Compare robustness performance across different
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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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develop a model for the analysis of the bridging between critical communications with railway communications in 5G networks by analysing the commonalities and the differences. The workplan should develop as
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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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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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Computer Science and Engineering Experience on programming languages such as Python, Java and Go Knowledge of cyber security techniques for overlay networks EVALUATION CRITERIA The selection will be based
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: OBJECTIVES | FUNCTIONS Create a Local Area Network in which laboratory equipment has fixed IP addresses - Use SCPI (Standard Commands for Programmable Instruments) commands accepted by each laboratory device
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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