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using Learning Algorithms & Dialog Data (S.H.I.E.L.D.)”. They will be required to: (a) develop machine learning models to predict optimal rehabilitation solutions; (b) use AI algorithms to detect
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secure, regulatory-compliant development platforms capable of ingesting, curating and continuously learning from multi-center hepatocellular carcinoma datasets; (c) create innovative algorithms/systems
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machine learning-enhanced algorithm incorporating domain knowledge for sustainable maritime transport”. Qualifications Applicants should have: (a) an honours degree, preferably in mathematics, logistics
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- “Secure and differentially private tree boosting on distributed datasets”. Qualifications Applicants should have an honours degree or an equivalent qualification. Applicants are invited to contact Prof
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) write code and conduct research on causal reasoning, bias mitigation and interpretability in Large Language Models (LLM); (b) design and implement algorithms or frameworks for enhancing
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the throughput and reliability of Low-Power Wide-Area Networks; (b) implement algorithms and carry out performance evaluation; and (c) perform any other duties as assigned by the project leader, the Head of
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) develop and distribute comprehensive learning materials to the students; (b) co-deliver software (CLO 3D) instruction and provide expert support; (c) analyse data and assist in evaluating