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includes, but is not limited to: photonic data processing and communication systems; AI-driven optical signal processing and network optimisation; machine learning for photonic systems modelling, control
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, interpretable machine learning, trustworthy and responsible AI, and the integration of NLP and XAI methods into complex systems and decision-support platforms. The successful candidate is expected to develop
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FAIR principles, combined with skills in statistical analysis, machine learning and/or data science. Experience with programming languages such as R, Python, or similar will be considered an advantage
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trustworthiness of AI systems. Key research directions include (but not limited to): adversarial machine learning, data poisoning and model manipulation, secure and privacy-preserving AI, trustworthy and
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accordance with FAIR principles, combined with skills in statistical analysis, machine learning and/or data science. Experience with programming languages such as R, Python, or similar will be considered
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to contribute to a project at the intersection of biotechnology, drug development, and computational analysis. Candidate will be involved in: Collaborating with computer scientists and engineers to develop AI