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. Preferential Factors Knowledge of machine learning, information retrieval, and natural language processing. Experience with conversational models and systems. Knowledge of Large Language Models (LLMs) and Large
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-Adapted Transformer Model incorporating Hybrid Linguistic-Contextual and Anomaly-based features. To evaluate the model against traditional and general deep learning models using comprehensive de facto
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 4 days ago
simulations and models. Workplan involved construction of chemical networks and analyzing them. Additional topics may include exploring those replicators’ errors. The success of this project will teach us about
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EXPERIMENTAL, NUMERICAL AND MACHINE LEARNING”, funded by the “Programme, Innovation and Digital Transition (Compete 2030), European Regional Development Fund FEDER and national funds, Portugal 2030, Foundation
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(optional). Scholarship contracts do not generate legal-labor relations or the provision of services, and the grantee does not acquire the status of worker in public functions. Policy of non-discrimination
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(20th of July 2026). Academic background: You must have an honours degree or demonstrated equivalent research expertise in computer science, machine learning, data science, human-computer interaction (HCI
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offering solutions to complex problems and creating new possibilities. At La Trobe, our students gain essential skills in programming, data analysis, and machine learning, equipping them to shape the future
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at the University of Melbourne. Learn more How can we help? Find a scholarship View scholarship guide FAQ Contact us
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support, advice and what to expect living and studying as an international student at the University of Melbourne. Learn more How can we help? Find a scholarship View scholarship guide FAQ Contact us
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on the development of methodologies and techniques of Evolutionary Computation and Machine Learning. V - Initial grant duration: 3 months V.I - Renewal Possibility: Possibily renewable VI - Funding and financial