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for brain signal acquisition Implementing an on-chip neuromorphic processor with a spike encoder and spiking neural network Developing a low-power spike-based transmitter. Setting up measurement systems and
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temporarily, as needed, when needed. The goal of this project is to advance the understanding of how working memory is implemented in the human brain. To this end, the main objective is to develop a neural
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inductive biases, we aim to identify key mechanisms that drive rapid learning in the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics
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machine learning frameworks such as recurrent neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection
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neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection. Comparison with known analytic methods and
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. Through academic, clinical, and industry partnerships, as well as global networks, we strive to translate biological discoveries into applications that enable the early detection of deviations from health
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directions will be pursued to enhance column generation using machine learning. The first line of research focuses on improving scalability by using Graph Neural Networks to identify and eliminate non
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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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theoretical research is focused on embodied neuroAI, recognising that the body influences biological neural networks, the continuity of actions, and sensory inputs. Leveraging advancements in Drosophila genetic