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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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computational and machine learning approaches, you will decipher genomic regulatory programs and infer the evolutionary patterns of gene regulatory networks in cortical neurons, study their developmental origin
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researcher to join our enthusiastic and young interdisciplinary teams of Prof. Dmitriev (Tissue Engineering and Biomaterials Group) and Prof. Vergult (Functional Genomics lab), as part of the MINDFUL research
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the Controllosphere Theory of cognitive effort (see doi 10.1037/rev0000467). A Ph.D. and background in computational modeling, engineering or a related discipline is required; expertise with linear control theory and
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. Applications will be accepted until the position is filled. Job profile The successful candidate will apply linear control theory to existing artificial neural network models of working memory, task switching
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researcher to join our enthusiastic and young interdisciplinary teams of Prof. Dmitriev (Tissue Engineering and Biomaterials Group) and Prof. Vergult (Functional Genomics lab), as part of the MINDFUL research