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. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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Modelling, Applied Statistics, Linguistics, Data Analysis, Large Language Models, Machine Learning. Start date: 1st October 2026 Deadline: 30th April Duration: 36 months Funding: Funded Funding towards
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-resolution (SR) technologies influence human and machine-based facial identification. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: 1. Do SR
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publications or conference presentations (either as first-author or as a co-author) Machine learning and/or computational modelling experience Experience with brain network modelling and analysis Experience
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to
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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights
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, and advanced machine learning in the engineering domain. Generative AI substantially changes the way engineers interact with and benefit from AI and access domain-specific knowledge, marking a phase
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information theory, and quantum technologies. For additional information, please visit: https://dakic.univie.ac.at/ . Your future tasks: You will actively participate in research, teaching & administration
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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights