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different methods of analysis used in the community, in particular linguistic probes (classifiers trained to predict certain linguistic properties from representations discovered by neural networks
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implementations (e.g., biophysical models), as well as models of machine intelligence (e.g., deep convolutional neural networks). We test the models' predictions in our empirical studies with human participants
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of responses to images and model these representations with AI models (deep neural networks (including topographical), multimodal models, Large Language Models), 2) define and model dimensions related
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neural networks on synchronised video, audio, and text data to automatically detect how gestures or gaze contribute to meaning in conversations.- Bridging cognitive science and AI to model how humans
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techniques and neural network techniques to adjust high-resolution X-ray spectra and infer physical properties of the emitting plasma. · Developing algorithms that optimise the adjustment of high-resolution X
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(at least in Python and C++); ideally strong hands-on experience with ROS2. Experience in AI development, especially with neural networks. Experience with standard software development tools (Git, CI/CD, IDEs