14 postdoctoral-image-processing-in-computer-science PhD positions at Trinity College Dublin
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biology and protein biochemistry techniques, confocal laser scanning microscopy, and live cell imaging with automated fluorescence microscopes are routinely used in the research group to investigate and
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support and integrate the successful candidate into a vibrant doctoral programme at TCD. PhD students at the department are embedded in the interdisciplinary context of the School of Social Sciences and
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with existing 3D image data Application Procedure Application Deadline: 29 June 2026 Applicants should submit a completed application package to: Name: Gareth W. Young, Assistant Professor (Graphics and
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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop
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with existing 3D image data. Application Procedure Application Deadline: 29 June 2026 Applicants should submit a completed application package to: Name: Nils Peters, Assistant Professor School: School
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explore new mathematical and computational approaches to represent such systems, drawing on ideas from stochastic processes, four-dimensional (space-time) modelling, complex systems, agent-based modelling
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tools. The PhD will be supervised within the Department of Civil, Structural and Environmental Engineering and will involve close collaboration with postdoctoral researchers and project partners, as
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Hospital and the School of Nursing and Midwifery is offering one part-time funded scholarships for entry into the PhD programme March or September 2027. The scholarships are open to nurses and midwives who
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held in the School of Engineering and Discipline of Mechanical, Manufacturing and Biomedical Engineering, Trinity College Dublin. Application Procedure• The application is in two parts. 1. Please
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sustainable catalyst platforms. This PhD project, Data-enhanced Quantum Chemistry for Predictive Catalyst Design, aims to Develop computational approaches for the discovery of sustainable catalysts based on low