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. Skills Terms programming; R; Python; Statistical methods; machine learning; differential expression; bulk RNAseq; scRNAseq; Linux/unix; spatial transcriptomics URLs/references https://ramialison
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-Ouellette, S., & Rudzicz, F. (2021). BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data. Frontiers in human neuroscience . [2] https
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-Ouellette, S., & Rudzicz, F. (2021). BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data. Frontiers in human neuroscience . [2] https
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Primary supervisor Adamu Muhammad Buhari Research area Machine Learning Vision-Language-Action (VLA) models are changing the way robots perceive their surroundings, interpret instructions, reason
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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ultimately shifts in species' distributions. This project harnesses research in ecological and agent-based modelling, machine learning, and AI to increase the predictive power of models of species
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dataset or benchmark to support reproducibility and comparison with future work. The work is expected to lead to publications in established computer vision, machine learning, artificial intelligence, and
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Primary supervisor David Dowe Co-supervisors Ron Firestein Research area Machine Learning The proposed PhD project aims to build a machine learning/deep learning-based decision support system that
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Primary supervisor David Dowe Co-supervisors Ron Firestein Research area Machine Learning The proposed PhD project aims to build a machine learning/deep learning-based decision support system that
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programming background with fundamentals in machine learning and data science. Experience in building visualisations and interactive immersive environments (using game engines like Unity3D) is