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networks.The candidate will collaborate with Dr. Rita Pucci (LIACS), Prof. Fons Verbeek (LIACS) and Prof. Daniele Avitabile (VU). This project aims to create in a deep neural network with a strong prior
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approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat
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. Work on this project will require research into novel methods that extract information from text that can be combined with the acoustic training data to inform flexible neural network structures and
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systems (CDSSs), so that their use in the clinic can be subject to rigorous quality control and certification. In this position, you will work on exploring synergies between Bayesian networks and AutoML
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Primary supervisor – Prof Tracey Chapman Ever-increasing numbers of older people across the world are spending their later years in poor health. Therefore, novel interventions to preserve the health
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, using principles of differential cryptanalysis. Analyze security of ML models against attacks that aim to recover parameters of the model (e.g., weights of a neural network). Investigate whether it is
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convolutional/neural networks Experience with explainable and interpretable AI (XAI) Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University’s rules
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network activity, Neuroscience research, Human cortical organoids, Synaptic plasticity, Brain organoids, Neural plasticity, Human neural networks, Neurobiology, Electrophysiology Financial Support This
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/f/d, E13 TV-L, 50-75%) The position is limited for three years. Description of the project The research group of Prof. Dr. Frank Schreiber at the University of Tübingen deals with the physics
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In