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the full complexity of fabrication processes and enable optimisation before physical manufacturing begins. This project aims to develop advanced deep learning models capable of predicting fabrication
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latitudes and deep convection in marine and continental environments). You will work closely with colleagues at Leeds and Warwick (who are developing and validating the toy/atomistic models) to translate
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
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or machine learning. Excellent programming skills in Python and deep learning frameworks A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal
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000 individuals in UK. As part of a wider strategy to develop a deep human experimental medicines platform, this project aims to mainly focus on using novel human in vitro platforms using IBD gut stem
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/unsupervised learning (regression, classification, clustering), ensemble methods, and deep learning architectures (CNNs, RNNs). Experience with explainable AI (e.g., SHAP, LIME) and radiomics preferred