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of a GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI (PhD Project) Explainability and Compact representation of K
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used will the information-theoretic Bayesian minimum message length (MML) principle. Student cohort PhD, possibly Master’s (Minor Thesis) or Honours URLs/references Chen, Li and Gao, Jiti and Vahid
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techniques for annotation, active learning (based on either deep learning or Bayesian learning), semi-supervised learning, transfer learning, imitation learning, etc., aiming to ensure the data and models
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Resource-Constrained Devices Bayesian Generative AI (PhD Project) Explainability and Compact representation of K-MDPs Creating a 21st Century Helpline for Enhanced Support and Continuity of Care Authorised
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. Butler, C. Goncu, and L. Holloway. Tactile presentation of network data: Text, matrix or diagram? In CHI2020, pages 1–12, 2020. I. Zukerman et al.˙Exploratory Interaction with a Bayesian Argumentation
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ICU care globally. About You You have a background in clinical or health research and a proven track record in project delivery. You thrive in complex, fast-paced environments and love working with
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in diverse, real-world environments. Both classical machine learning methods and deep learning techniques can be employed to tackle this task. This project aims to achieve several objectives: 1
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doctoral qualification and/or recognised significant experience in the relevant discipline area and have a proven track record of obtaining external research grants, a strong publication record, and a
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/primary care/public health research Demonstrated statistical analysis and manuscript and research proposal preparation skills; including a solid track record of refereed research publications Advanced
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, Python, and/or C++) A strong track record of research output, including journal publications and conference contributions Expertise or strong interest in one or more of the following areas: Computational