The CSNG Lab at the Faculty of Mathematics and Physics at the Charles University is seeking a highly motivated Postdoctoral Researcher to join our team to work on a digital twin model of the visual system. Funded by the JUNIOR Post-Doc Fund, this position offers an exciting opportunity to conduct cutting-edge research at the intersection of systems neuroscience, computational modeling, and AI. The project involves developing novel modular, multi-layer recurrent neural network (RNN) architectures that directly mirror the architecture of the primary visual cortex. Our models will establish a one-to-one mapping between individual neurons at different stages of the visual pathway and their artificial counterparts. They will explicitly incorporate functionally specific lateral recurrent interactions, excitatory and inhibitory neuronal classes, complex single-neuron transfer functions with adaptive mechanisms, synaptic depression, and others. We will first train our new RNNs on synthetic data generated by a state-of-the-art biologically realistic recurrent spiking model of the primary visual cortex developed in our group. After establishing the proof-of-concept on the synthetic data, we will translate our models to publicly available mouse and macaque data, as well as additional data from our experimental collaborators.