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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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. PhD Project Description Project Title: Photonic-Inspired Federated Learning for Communication-Efficient Next Generation Radio Access Networks (NG-RANs) Description: This PhD project will develop a novel
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. Quantitative, computational, or mixed-method approaches are particularly encouraged, including but not limited to geospatial analysis, machine learning, predictive modelling, and causal inference techniques
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. There will be a requirement to teach in undergraduate laboratories and tutorials as part of the scholarship. Tasks: The successful candidate will be involved in: 1. Applying first-principles and machine
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the application of machine learning and artificial intelligence. By using neural networks developed in Python, the project aims to generate robust and generalisable models for scaffold design. Industrial
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valued and empowered to thrive. Our dedication to these values ensures that we foster a culture of mutual respect, open collaboration, continuous learning, and innovative thinking. Join us at RCSI, where