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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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of Pharmacy, UCC, led by the Professor of Pharmaceutics, Brendan Griffin is aiming to develop Artificial Intelligence (AI) and machine learning tools that can accelerate the creation of medicines for conditions
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position is available to work in the area of Digital Twins for optical networks, making use of intelligent AI-driven control planes. The applicants should have a solid theoretical background on machine
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related Data Science area such as Biostatistics or Statistical/Machine Learning and have a track record of independent research of international standing. Reporting to the Head of School of Mathematical
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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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Maynooth University, National University of Ireland Maynooth; | Maynooth, Leinster | Ireland | 28 days ago
, analog, mixed signal), IC verification, artificial intelligence & machine learning, signal processing, hardware programming languages and digital systems, computing and programming etc. The successful
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technical knowledge in areas such as: Foundational Models Algorithmic Research Machine and Deep Learning Computer Vision Edge AI, TinyML, and Embedded AI Explainable AI Safe AI Federated, Parallel
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]. 3. Explore the diversity of signals and perform complementary experiments to finalize the training dataset [Month 6 – 12]. 4. Develop a data analysis process based on machine learning for multimodal
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of trial team • This role requires excellent communication and interpersonal skills, computer literacy, organization and an awareness of time management. This role will focus in particular
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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