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for analysing authentic, synthetic, and manipulated images or videos. The work will combine predictive performance with explainability, uncertainty estimation, robustness, and generalization. Attention will be
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detailed knowledge of the performance parameters that affect their application software, as it aids in making future technology choices, predicting performance and scalability, and adapting critical software
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of the performance parameters that affect their application software, as it aids in making future technology choices, predicting performance and scalability, and adapting critical software to new developments
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focus on combining simulations using spatial-genetic-demographic individual based models (e.g., using the software SLiM), machine learning approaches, and genomic data to estimate larval dispersal
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TOEFL or IELTS. To be considered for admission, applicants must have a minimum TOEFL score of 575 (written test)/233 (computer-based test)/90 (internet-based test) or a IELTS score of 6.5. In some cases
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-Computer Interaction (HCI) perspectives to investigate how AI companionship technologies may reshape experiences of care, companionship, emotional support, wellbeing, and autonomy among older adults. Your
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to identify key parameters influencing stope stability and dimensioning. Evaluate traditional empirical design methods and quantify their limitations in heterogeneous or structurally complex rock masses
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learning activities in courses related to communications and networking Required selection criteria You must have a relevant master’s degree in wireless communications and mobile networks, computer networks
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develop quantitative methods to estimate effects on infrastructure degradation, maintenance needs, operational risk, punctuality and costs. The aim is to develop and validate a practical, transparent
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other components. The PhD candidate will link TrainGate detections and early warnings with maintenance, incident, operational and cost data and develop quantitative methods to estimate effects