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, and computational models. This PhD position is centered on addressing these challenges through innovative computational methods, combining optical system design, signal processing, machine learning, and
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. Knowledge of: Global education models, including study abroad, study away, exchange partnerships, and international academic collaboration. Curriculum development and integration of global learning within
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aspects of quantitative data analysis: analysis of large/longitudinal datasets, latent variable modelling techniques, structural equation modelling – and strong motivation and curiosity to enlarge
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for mapping processes. Moreover, the successful candidate will support other activities in WP2 by integrating the models into AI-based perception systems, contributing to creating multi-modal ecological maps
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— the persistent perception of sound when no external source is present. Tinnitus can cause distress, anxiety, and loss of concentration, and current therapies are often costly, complex, or inaccessible
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machine-based facial recognition, and where do human and machine decisions diverge? Do SR methods perform equitably across demographic groups? Can SR models be improved using human perceptual insights
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work will entail: We are seeking an experienced post-doctoral researcher to produce rigorous, publication-quality research on consumer perceptions and preferences in two projects that focus
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-)distortion–reliability bounds, design adaptive codecs that prioritise safety-critical bits, and close the loop between information theory and AI models for cooperative perception; publishing research findings
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methods – ideally knowledge of several of the following aspects of quantitative data analysis: analysis of large/longitudinal datasets, latent variable modelling techniques, structural equation modelling
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liaison with other departments/agencies, both internal and external. Models positive collaboration/interaction with colleagues, management team, and other UAMS departments. Periodic travel and evening work