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researchers eager to contribute to this emerging scientific frontier. About the project The role of the PhD candidate will be to develop efficient methods for Hybrid Learning-Control Methods for Autonomous
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16th October 2026 Languages English English English The Department of Engineering Cybernetics has a vacancy for a PhD Candidate in Hybrid Learning-Control Methods for Autonomous Underwater
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research direction is the integration of strategic transport models, such as discrete choice modelling (DCM) with agent-based modelling (ABM), to examine potential transport behaviour under different
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reliability theory, probabilistic methods or statistics Strong computational skills, including programming (e.g., Python, MATLAB) and nonlinear finite element analysis (e.g., Abaqus, LS-DYNA) Knowledge
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on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured
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Ph.D. Programme with specialization in Economics, which trains students to engage in high quality scientific research, making use of economic theory and state of the art econometric methods
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Forest Inventory is looking for a PhD candidate to develop cutting-edge multimodal artificial intelligence methods for forest biodiversity mapping and monitoring. The project will investigate how
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the zebrafish forebrain during defined sensory stimulation paradigms. Functional response properties will be mapped onto anatomically identified circuit elements. Confocal Microscopy and Histology: Use confocal
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engagement with long-term climate futures differs across climate risks, Earth system tipping elements, audiences, social groups, professional communities, or political and cultural contexts studying how
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project focuses on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High