The candidate will develop new deep learning solutions, including convolutional neural networks, variational autoencoders, and generative adversarial networks, to build predictive models, particularly focused on cell type diversity in the brain and in cancer. These models will be used to gain mechanistic insight into normal and disease-related biological processes, hence the explainability of these models (XAI) is crucial. Depending on the interest, the candidate can be involved in projects related to evolution, regenerative medicine, and gene therapy. Finally, the position will allow to explore future interactions between neuroscience research and research in artificial neural networks.
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