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multiple brain areas in an optimised way. This may include neural network and neural mass modelling of large-scale brain activity during and after stimulation, and experimental tACS in healthy participants
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an optimised way. This may include neural network and neural mass modelling of large-scale brain activity during and after stimulation, and experimental tACS in healthy participants. The successful applicant
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personalized psychiatry, network science, and recovery-oriented research; Interest in integrating neural, behavioral, and recovery-related outcomes; Excellent communication skills and the ability to work in
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essential for addressing real-world problems. In particular, we will consider applications to neural network training, imaging, and the analysis and numerical solution of partial differential equations
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1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD position 2 will focus on designing scalable
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? Then check out the vacancy below and apply for a PhD position in this exciting research direction. Join Us! Modern deep learning is progressing fast. Yet even the most advanced neural networks are paired
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: Developing novel techniques to understand how information is processed within deep neural networks. Developing methods that achieve high accuracy while also being safe, interpretable, responsible, and reliable
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to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the successful candidate will be an integral part of the prestigious ERC
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to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the candidate will be an integral part of the prestigious NWO AiNED AI-on-ONN
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ensure Effective and Sustainable Health Care and Rehabilitation), is a new European Marie-Curie doctoral training network. Fifteen doctoral candidates will explore how individual differences shape brain