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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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on large annotated datasets. Memory-efficient deep learning: Model compression, pruning, quantisation, selective memory replay, and efficient training strategies. Energy-efficient deep learning: Methods
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– such as tandem neural networks , video diffusion models , and reinforcement learning – will be explored to efficiently navigate these high-dimensional, nonlinear design spaces. To achieve robust property
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the education/instructional videos contained within them. Therefore, you will be contributing to the development and refinement of a potential medical device that could become adopted into clinical
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Assessment Systems: Toward Trustworthy AI for Complex Educational Evaluation Image and Video Analysis Using Machine Learning Algorithms Mathematical and Computational Neuroscience, from neural data and network
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from video recordings. This studentship would be part-sponsored by an industrial partner, Neurotherapeutics Ltd. Use translational neuroimaging and neurophysiology methods together in a rodent model of
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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clearly described. Interviews will be conducted via video conferencing (e.g. MS Teams or similar) on Monday 15 December 2025. Interview support for those with disabilities will be available where required
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@aalto.fi ). Want to know more about us and your future colleagues? You can watch these videos: Aalto University – Towards a better world , Aalto People , and Shaping a Sustainable Future . Read more about